Job Description Job Title: Principal Agentic AI Architect Location: Charlotte, NC (Day 1 Onsite) Key Responsibilities Technical Leadership & Architecture Define and drive the long-term technology strategy for Financial Crime modernization initiatives. Lead the architecture and implementation of AI-powered investigation platforms, decisioning engines, and agentic workflows. Establish engineering standards, design patterns, and reference architectures across Financial Crime platforms. Serve as the highest-level technical reviewer for architecture, security, scalability, resiliency, and performance decisions. Lead technical design reviews and influence enterprise architecture direction. AI & Agentic Engineering Design and implement GenAI and Agentic AI solutions for: Investigator copilots Alert triage and disposition Risk assessment Entity resolution SAR narrative generation Customer screening Knowledge retrieval and decisioning Evaluate and implement modern AI frameworks, including LLM orchestration, agent frameworks, vector databases, RAG architectures, model routing, guardrails, and observability. Partner with Data Science teams to operationalize AI/ML models into scalable production platforms. Engineering Excellence Write and review high-quality production code when necessary. Lead proof-of-concepts, rapid prototyping, and technical spikes. Mentor senior engineers and establish software engineering best practices. Drive automation, CI/CD, DevSecOps, testing, and operational excellence. Resolve complex technical challenges across multiple platforms and teams. Platform Modernization Lead migration from legacy Financial Crime applications to cloud-native architectures. Architect scalable microservices, event-driven systems, and API-first platforms. Design enterprise capabilities for real-time risk assessment, customer screening, case management, regulatory reporting, AI orchestration, and data ingestion and processing. Drive modernization using cloud technologies and enterprise platforms. Stakeholder Partnerships Collaborate with Product, Compliance, Risk, Operations, Data Science, and Engineering leadership. Translate business needs into scalable technical solutions. Present architecture strategies and modernization roadmaps to senior technology executives. Required Qualifications 7+ years of engineering experience, or equivalent demonstrated through work experience, training, military experience, or education. 7+ years of experience architecting, designing, and leading the delivery of large-scale solutions. 4+ years of experience presenting technology strategy and concepts to C-level executives and large audiences. 5+ years of experience delivering cloud-ready and cloud-native solutions. Desired Qualifications 2+ years of experience developing or deploying AI-powered tools, chatbots, LLM-based automation, or agentic workflows, including understanding of AI risks, observability needs, and stakeholder communication. 4+ years of experience in the Financial Services industry. Excellent verbal, written, and interpersonal communication skills. Ability to prioritize work, meet deadlines, achieve goals, and work under pressure. Strong analytical skills and ability to solve complex technical problems. NLB Services is an Equal Opportunity Employer. All qualified applicants will receive consideration without regard to race, color, religion, sex (including pregnancy, sexual orientation and gender identity), national origin, age, disability, genetic information, protected veteran status, or any other characteristic protected by applicable law. NLB Services provides reasonable accommodations during the recruitment process as required by law. Applicants requiring an accommodation due to a disability, pregnancy-related limitation, or sincerely held religious belief, practice or observance may contact their recruiter or email .
10/29/2026
Full time
Job Description Job Title: Principal Agentic AI Architect Location: Charlotte, NC (Day 1 Onsite) Key Responsibilities Technical Leadership & Architecture Define and drive the long-term technology strategy for Financial Crime modernization initiatives. Lead the architecture and implementation of AI-powered investigation platforms, decisioning engines, and agentic workflows. Establish engineering standards, design patterns, and reference architectures across Financial Crime platforms. Serve as the highest-level technical reviewer for architecture, security, scalability, resiliency, and performance decisions. Lead technical design reviews and influence enterprise architecture direction. AI & Agentic Engineering Design and implement GenAI and Agentic AI solutions for: Investigator copilots Alert triage and disposition Risk assessment Entity resolution SAR narrative generation Customer screening Knowledge retrieval and decisioning Evaluate and implement modern AI frameworks, including LLM orchestration, agent frameworks, vector databases, RAG architectures, model routing, guardrails, and observability. Partner with Data Science teams to operationalize AI/ML models into scalable production platforms. Engineering Excellence Write and review high-quality production code when necessary. Lead proof-of-concepts, rapid prototyping, and technical spikes. Mentor senior engineers and establish software engineering best practices. Drive automation, CI/CD, DevSecOps, testing, and operational excellence. Resolve complex technical challenges across multiple platforms and teams. Platform Modernization Lead migration from legacy Financial Crime applications to cloud-native architectures. Architect scalable microservices, event-driven systems, and API-first platforms. Design enterprise capabilities for real-time risk assessment, customer screening, case management, regulatory reporting, AI orchestration, and data ingestion and processing. Drive modernization using cloud technologies and enterprise platforms. Stakeholder Partnerships Collaborate with Product, Compliance, Risk, Operations, Data Science, and Engineering leadership. Translate business needs into scalable technical solutions. Present architecture strategies and modernization roadmaps to senior technology executives. Required Qualifications 7+ years of engineering experience, or equivalent demonstrated through work experience, training, military experience, or education. 7+ years of experience architecting, designing, and leading the delivery of large-scale solutions. 4+ years of experience presenting technology strategy and concepts to C-level executives and large audiences. 5+ years of experience delivering cloud-ready and cloud-native solutions. Desired Qualifications 2+ years of experience developing or deploying AI-powered tools, chatbots, LLM-based automation, or agentic workflows, including understanding of AI risks, observability needs, and stakeholder communication. 4+ years of experience in the Financial Services industry. Excellent verbal, written, and interpersonal communication skills. Ability to prioritize work, meet deadlines, achieve goals, and work under pressure. Strong analytical skills and ability to solve complex technical problems. NLB Services is an Equal Opportunity Employer. All qualified applicants will receive consideration without regard to race, color, religion, sex (including pregnancy, sexual orientation and gender identity), national origin, age, disability, genetic information, protected veteran status, or any other characteristic protected by applicable law. NLB Services provides reasonable accommodations during the recruitment process as required by law. Applicants requiring an accommodation due to a disability, pregnancy-related limitation, or sincerely held religious belief, practice or observance may contact their recruiter or email .
Candidates must be authorized to work in the United States without the need for current or future visa sponsorship. " This position is for full-time, onsite employment at the Family Dollar Chesapeake, VA Store Support Center. " General Summary: The Manager of Vendor Governance, FinOps, Asset Management & Contract Management serves as the centralized control-plane governance function within Family Dollar's Infrastructure Engineering organization. This is a unique, high-trust role designed with intentional independence - operating without dedicated direct reports to preserve separation of duties, eliminate conflicts of interest, and ensure objective oversight across all infrastructure engineering teams and BPO partners. This role provides the VP of Infrastructure Engineering & Operations with an independent, consolidated view of vendor performance, technology spend, asset health, and contractual obligations across all domains: Hybrid Cloud, Network Engineering, Automation, and Retail/Edge environments. It is the single source of truth for governance intelligence across a multi million infrastructure portfolio spanning 7,400+ stores, 9 distribution centers, 2 data centers, and 3 public cloud platforms. This is not an operational role. It is a governance, intelligence, and accountability function - one that provides executive-level visibility and keeps the infrastructure organization disciplined, cost-effective, and contractually sound. Principal Duties & Responsibilities: Vendor Governance & Performance Management Own the vendor governance framework for all infrastructure technology vendors and service providers Track and report on vendor SLA/KPI compliance across BPO, telecom, hardware, software, and cloud vendors Lead vendor performance reviews (QBRs, MBRs) and escalate performance gaps to the VP and relevant directors Maintain a vendor risk register and flag concentration risks, single-vendor dependencies, and end-of-life exposures Evaluate vendor roadmaps and alignment with Family Dollar's technology strategy Serve as an independent governance bridge between engineering teams and BPO partners - not embedded in either FinOps & Cost Optimization (Cloud + On-Premises) Lead FinOps practice across Azure, GCP, OCI, and on-premises infrastructure Own cost visibility dashboards, chargeback/showback models, and monthly spend reporting for the VP Identify and drive cost optimization opportunities: reserved instances, rightsizing, idle resource elimination, and license rationalization Define and enforce cloud cost governance policies in partnership with engineering teams Monitor cloud spend anomalies and alert leadership to budget variances in real time Maintain multi-year infrastructure cost forecasts and support annual budgeting cycles Partner with Finance to align infrastructure spend to business unit cost allocations Asset Management & Lifecycle Governance Own the end-to-end IT asset lifecycle governance process: procurement, deployment, tracking, and decommission Ensure CMDB accuracy and completeness as the authoritative system of record for all infrastructure assets Maintain hardware refresh schedules and lifecycle dashboards across stores, DCs, data centers, and cloud Partner with engineering teams to identify EoL/EoS risks and drive proactive refresh planning Govern software license entitlements and utilization to prevent compliance exposure Validate BPO asset inventory reporting and reconcile against procurement records Track and report on asset financial depreciation schedules in partnership with Finance Contract Management & Procurement Governance Own and manage all infrastructure technology contracts: renewal calendars, terms, SLAs, and obligations Lead contract renewals, amendments, and renegotiations in partnership with Legal, Procurement, and Finance Maintain a centralized contract repository with renewal triggers, expiration tracking, and risk flags Evaluate vendor proposals and new contracts to ensure alignment with technical and financial requirements Identify contract optimization opportunities: consolidation, renegotiation, and elimination of redundant agreements Enforce contract SLA commitments and hold vendors accountable through structured performance reviews Support RFP / RFI processes for infrastructure technology procurements Executive Reporting & Governance Intelligence Produce monthly and quarterly infrastructure governance dashboards for the VP, covering: vendor health, cost posture, asset lifecycle status, and contract obligations Maintain a unified governance scorecard across all infrastructure domains Prepare executive briefings, board-level summaries, and business case materials as needed Identify and escalate emerging governance risks: compliance gaps, cost overruns, vendor failures, and contractual exposure Develop and maintain governance policies, standards, and procedures for vendor, asset, and contract management BPO Oversight & Accountability Independently validate BPO performance against contracted SLAs and KPIs - separate from engineering directors Audit BPO invoices against contracted rates and service delivery Maintain a BPO performance scorecard and present findings to the VP on a regular cadence Identify BPO delivery gaps and work with the VP to initiate corrective action plans Track BPO-driven cost savings and efficiency commitments against actuals Security & Compliance Governance Support Maintain a mapping of infrastructure assets and vendors to regulatory and compliance frameworks (PCI-DSS, SOX) Track patch compliance and remediation SLAs across managed infrastructure domains Support audit readiness by maintaining governance documentation, contract evidence, and asset records Flag vendor or asset lifecycle risks that create compliance exposure Position Requirements Technical Knowledge Solid understanding of cloud platforms (Azure, GCP, OCI) and hybrid cloud cost structures Familiarity with enterprise infrastructure domains: networking, compute, storage, backup, and cloud Working knowledge of CMDB tooling (ServiceNow or equivalent) and asset lifecycle processes Understanding of software licensing models (perpetual, subscription, consumption-based) Proficiency with FinOps tooling and cloud cost management platforms (e.g., Apptio, CloudHealth, native cloud billing) Governance & Commercial Skills Proven expertise in contract lifecycle management: negotiation, renewal, compliance enforcement Experience building and executing vendor governance frameworks including SLA tracking and QBRs FinOps practitioner experience: chargeback, showback, reserved instance strategy, rightsizing Ability to develop executive-ready dashboards, governance reports, and financial models Strong analytical skills - able to synthesize complex data into actionable insights Familiarity with IT procurement and sourcing best practices Minimum Requirements: Education & Experience Bachelor's degree in Business, Information Technology, Finance, or a related field 8+ years of experience in IT governance, vendor management, FinOps, or IT asset management - within a large enterprise environment 3+ years in a role with direct accountability for technology contracts, vendor performance, or infrastructure cost management Experience operating in a multi-vendor, BPO-partnered IT delivery model Exposure to large-scale retail or distributed enterprise environments strongly preferred Preferred Qualifications: FinOps Certified Practitioner (FinOps Foundation) ITIL v4 Certification - Asset Management or Service Management tracks Certified Technology Procurement Professional (CTPP) or equivalent IAITAM Certified Asset Manager (ICAMP or CHAMP) Experience with ServiceNow ITAM/SAM, Flexera, or Snow Software Prior experience at a large-format retailer (Dollar General, Walmart, Target, etc.) Exposure to TSA (Transition Service Agreement) governance environments "Projected Salary Range: $120,000 - $135,000". Family Dollar is an equal opportunity employer and committed to recruiting, hiring, training, and promoting qualified people of all backgrounds, and makes all employment decisions without regard to any protected status. We are committed to complying with the Americans with Disabilities Act (ADA) and providing reasonable accommodations to qualified individuals with disabilities. Full time 510 Volvo Parkway,Chesapeake,Virginia 23320 IT Security Family Dollar
10/29/2026
Full time
Candidates must be authorized to work in the United States without the need for current or future visa sponsorship. " This position is for full-time, onsite employment at the Family Dollar Chesapeake, VA Store Support Center. " General Summary: The Manager of Vendor Governance, FinOps, Asset Management & Contract Management serves as the centralized control-plane governance function within Family Dollar's Infrastructure Engineering organization. This is a unique, high-trust role designed with intentional independence - operating without dedicated direct reports to preserve separation of duties, eliminate conflicts of interest, and ensure objective oversight across all infrastructure engineering teams and BPO partners. This role provides the VP of Infrastructure Engineering & Operations with an independent, consolidated view of vendor performance, technology spend, asset health, and contractual obligations across all domains: Hybrid Cloud, Network Engineering, Automation, and Retail/Edge environments. It is the single source of truth for governance intelligence across a multi million infrastructure portfolio spanning 7,400+ stores, 9 distribution centers, 2 data centers, and 3 public cloud platforms. This is not an operational role. It is a governance, intelligence, and accountability function - one that provides executive-level visibility and keeps the infrastructure organization disciplined, cost-effective, and contractually sound. Principal Duties & Responsibilities: Vendor Governance & Performance Management Own the vendor governance framework for all infrastructure technology vendors and service providers Track and report on vendor SLA/KPI compliance across BPO, telecom, hardware, software, and cloud vendors Lead vendor performance reviews (QBRs, MBRs) and escalate performance gaps to the VP and relevant directors Maintain a vendor risk register and flag concentration risks, single-vendor dependencies, and end-of-life exposures Evaluate vendor roadmaps and alignment with Family Dollar's technology strategy Serve as an independent governance bridge between engineering teams and BPO partners - not embedded in either FinOps & Cost Optimization (Cloud + On-Premises) Lead FinOps practice across Azure, GCP, OCI, and on-premises infrastructure Own cost visibility dashboards, chargeback/showback models, and monthly spend reporting for the VP Identify and drive cost optimization opportunities: reserved instances, rightsizing, idle resource elimination, and license rationalization Define and enforce cloud cost governance policies in partnership with engineering teams Monitor cloud spend anomalies and alert leadership to budget variances in real time Maintain multi-year infrastructure cost forecasts and support annual budgeting cycles Partner with Finance to align infrastructure spend to business unit cost allocations Asset Management & Lifecycle Governance Own the end-to-end IT asset lifecycle governance process: procurement, deployment, tracking, and decommission Ensure CMDB accuracy and completeness as the authoritative system of record for all infrastructure assets Maintain hardware refresh schedules and lifecycle dashboards across stores, DCs, data centers, and cloud Partner with engineering teams to identify EoL/EoS risks and drive proactive refresh planning Govern software license entitlements and utilization to prevent compliance exposure Validate BPO asset inventory reporting and reconcile against procurement records Track and report on asset financial depreciation schedules in partnership with Finance Contract Management & Procurement Governance Own and manage all infrastructure technology contracts: renewal calendars, terms, SLAs, and obligations Lead contract renewals, amendments, and renegotiations in partnership with Legal, Procurement, and Finance Maintain a centralized contract repository with renewal triggers, expiration tracking, and risk flags Evaluate vendor proposals and new contracts to ensure alignment with technical and financial requirements Identify contract optimization opportunities: consolidation, renegotiation, and elimination of redundant agreements Enforce contract SLA commitments and hold vendors accountable through structured performance reviews Support RFP / RFI processes for infrastructure technology procurements Executive Reporting & Governance Intelligence Produce monthly and quarterly infrastructure governance dashboards for the VP, covering: vendor health, cost posture, asset lifecycle status, and contract obligations Maintain a unified governance scorecard across all infrastructure domains Prepare executive briefings, board-level summaries, and business case materials as needed Identify and escalate emerging governance risks: compliance gaps, cost overruns, vendor failures, and contractual exposure Develop and maintain governance policies, standards, and procedures for vendor, asset, and contract management BPO Oversight & Accountability Independently validate BPO performance against contracted SLAs and KPIs - separate from engineering directors Audit BPO invoices against contracted rates and service delivery Maintain a BPO performance scorecard and present findings to the VP on a regular cadence Identify BPO delivery gaps and work with the VP to initiate corrective action plans Track BPO-driven cost savings and efficiency commitments against actuals Security & Compliance Governance Support Maintain a mapping of infrastructure assets and vendors to regulatory and compliance frameworks (PCI-DSS, SOX) Track patch compliance and remediation SLAs across managed infrastructure domains Support audit readiness by maintaining governance documentation, contract evidence, and asset records Flag vendor or asset lifecycle risks that create compliance exposure Position Requirements Technical Knowledge Solid understanding of cloud platforms (Azure, GCP, OCI) and hybrid cloud cost structures Familiarity with enterprise infrastructure domains: networking, compute, storage, backup, and cloud Working knowledge of CMDB tooling (ServiceNow or equivalent) and asset lifecycle processes Understanding of software licensing models (perpetual, subscription, consumption-based) Proficiency with FinOps tooling and cloud cost management platforms (e.g., Apptio, CloudHealth, native cloud billing) Governance & Commercial Skills Proven expertise in contract lifecycle management: negotiation, renewal, compliance enforcement Experience building and executing vendor governance frameworks including SLA tracking and QBRs FinOps practitioner experience: chargeback, showback, reserved instance strategy, rightsizing Ability to develop executive-ready dashboards, governance reports, and financial models Strong analytical skills - able to synthesize complex data into actionable insights Familiarity with IT procurement and sourcing best practices Minimum Requirements: Education & Experience Bachelor's degree in Business, Information Technology, Finance, or a related field 8+ years of experience in IT governance, vendor management, FinOps, or IT asset management - within a large enterprise environment 3+ years in a role with direct accountability for technology contracts, vendor performance, or infrastructure cost management Experience operating in a multi-vendor, BPO-partnered IT delivery model Exposure to large-scale retail or distributed enterprise environments strongly preferred Preferred Qualifications: FinOps Certified Practitioner (FinOps Foundation) ITIL v4 Certification - Asset Management or Service Management tracks Certified Technology Procurement Professional (CTPP) or equivalent IAITAM Certified Asset Manager (ICAMP or CHAMP) Experience with ServiceNow ITAM/SAM, Flexera, or Snow Software Prior experience at a large-format retailer (Dollar General, Walmart, Target, etc.) Exposure to TSA (Transition Service Agreement) governance environments "Projected Salary Range: $120,000 - $135,000". Family Dollar is an equal opportunity employer and committed to recruiting, hiring, training, and promoting qualified people of all backgrounds, and makes all employment decisions without regard to any protected status. We are committed to complying with the Americans with Disabilities Act (ADA) and providing reasonable accommodations to qualified individuals with disabilities. Full time 510 Volvo Parkway,Chesapeake,Virginia 23320 IT Security Family Dollar
Job Description Principal Software Engineer - C#/.NET Core & AWS AI-Enabled Platforms $200,000 - $240,000 + bonus & RSUs Hybrid (3-days in office) I'm recruiting for a global leader in professional information and enterprise software, and they need a hands-on Principal Engineer to help modernise a major U.S. tax compliance platform. The opportunity This is a true Principal IC role: you'll own architecture and technical direction for large-scale production systems, shape decisions across multiple engineering teams, and stay close to the code. No ivory tower. What you'll do Own architecture and system design for complex, high-scale platforms, balancing scalability, reliability, performance and security Build production software in C#/.NET Core on AWS, staying hands-on in design, delivery and problem-solving Lead the move from legacy applications to cloud-native architectures: microservices, APIs, distributed systems and containerised workloads Set technical direction and influence engineering decisions across teams Mentor through design reviews, code guidance and best practice Identify and deliver practical uses of AI/ML and Generative AI in production products Help shape the long-term technical roadmap and communicate trade-offs and risks What you'll bring 10+ years in software engineering, with proven Principal-level (or equivalent senior IC) scope Strong, recent, hands-on C#/.NET Core experience Deep production AWS experience across services such as EC2, S3, ELB, Auto Scaling, RDS, Lambda, SQS and container services A track record of architecting and building large-scale distributed systems, microservices and highly available applications Experience modernising complex legacy systems into resilient, cloud-native solutions Strong grounding in architecture, OO design, algorithms, design patterns, API design and relational databases Excellent communication, able to influence across Product, Engineering, Security, QA, Data and Ops Degree in Computer Science or a related field, or equivalent experience
10/29/2026
Full time
Job Description Principal Software Engineer - C#/.NET Core & AWS AI-Enabled Platforms $200,000 - $240,000 + bonus & RSUs Hybrid (3-days in office) I'm recruiting for a global leader in professional information and enterprise software, and they need a hands-on Principal Engineer to help modernise a major U.S. tax compliance platform. The opportunity This is a true Principal IC role: you'll own architecture and technical direction for large-scale production systems, shape decisions across multiple engineering teams, and stay close to the code. No ivory tower. What you'll do Own architecture and system design for complex, high-scale platforms, balancing scalability, reliability, performance and security Build production software in C#/.NET Core on AWS, staying hands-on in design, delivery and problem-solving Lead the move from legacy applications to cloud-native architectures: microservices, APIs, distributed systems and containerised workloads Set technical direction and influence engineering decisions across teams Mentor through design reviews, code guidance and best practice Identify and deliver practical uses of AI/ML and Generative AI in production products Help shape the long-term technical roadmap and communicate trade-offs and risks What you'll bring 10+ years in software engineering, with proven Principal-level (or equivalent senior IC) scope Strong, recent, hands-on C#/.NET Core experience Deep production AWS experience across services such as EC2, S3, ELB, Auto Scaling, RDS, Lambda, SQS and container services A track record of architecting and building large-scale distributed systems, microservices and highly available applications Experience modernising complex legacy systems into resilient, cloud-native solutions Strong grounding in architecture, OO design, algorithms, design patterns, API design and relational databases Excellent communication, able to influence across Product, Engineering, Security, QA, Data and Ops Degree in Computer Science or a related field, or equivalent experience
About the role: • We're seeking a Principal Backend Engineer to set the technical vision for our backend platform and drive its architecture, service design, and delivery across multiple teams. • Our backend is built as Go-based microservices, and you'll be the technical authority on how those services are designed, built, operated, and evolved. • You'll operate at the intersection of engineering, product, and architecture - shaping not just how services get built, but what gets prioritized and why. • You'll own the API and event contracts that the front end and other systems depend on, and hold end-to-end accountability for the platform's engineering foundations: service boundaries, data modeling, reliability, observability, performance, security, and testing strategy. • You'll also be a force multiplier for the engineering org - raising the technical bar through mentorship, architecture reviews, and by modeling how ambiguous, cross-team problems get solved.
10/28/2026
Full time
About the role: • We're seeking a Principal Backend Engineer to set the technical vision for our backend platform and drive its architecture, service design, and delivery across multiple teams. • Our backend is built as Go-based microservices, and you'll be the technical authority on how those services are designed, built, operated, and evolved. • You'll operate at the intersection of engineering, product, and architecture - shaping not just how services get built, but what gets prioritized and why. • You'll own the API and event contracts that the front end and other systems depend on, and hold end-to-end accountability for the platform's engineering foundations: service boundaries, data modeling, reliability, observability, performance, security, and testing strategy. • You'll also be a force multiplier for the engineering org - raising the technical bar through mentorship, architecture reviews, and by modeling how ambiguous, cross-team problems get solved.
Job Title: Senior / Principal Solution Architect - Contact Center Duration: Long term Job Type: C2C/W2/1099 Location: Remote Primary Skills: NICE CXone, Amazon Connect (AWS), Siera Role Overview We are looking for an experienced End-to-End Contact Center Solution Architect with deep expertise in NICE CXone, Siera and Amazon Connect to lead enterprise contact center transformation initiatives. The architect will be responsible for solution discovery, architecture, design, integration, implementation, migration, and deployment of cloud-based omnichannel contact center platforms. The ideal candidate must have strong hands-on architecture experience, particularly integrating contact center platforms with Salesforce Service Cloud, enterprise applications, and AI-powered customer service solutions. Hiring Preference: Candidates with expertise across NICE CXone, Siera, Amazon Connect, Salesforce Service Cloud, and AI-enabled contact center transformation will be prioritized. Key Responsibilities Own end-to-end solution architecture for NICE CXone and Amazon Connect implementations, modernization, and migration programs. Design enterprise contact center capabilities, including IVR, ACD, CTI, omnichannel routing, inbound/outbound calling, and digital engagement. Architect Salesforce Service Cloud integrations, including agent desktop, screen pops, customer 360, case management, and workflow automation. Design conversational AI, virtual agents, intelligent routing, agent assist, real-time transcription, call summarization, and sentiment analysis solutions. Define integration architecture using AWS Lambda, Lex, Bedrock, API Gateway, REST APIs, and event-driven services. Lead legacy contact center migrations, telephony integrations, data migration, testing, cutover, and production deployment. Develop high-level and low-level architecture, integration specifications, solution estimates, and implementation roadmaps. Ensure security, scalability, high availability, disaster recovery, performance, and regulatory compliance. Provide technical leadership to engineering teams and collaborate with business stakeholders, enterprise architects, and client leadership. Required Technical Skills NICE CXone / Siera: ACD, Studio, IVR, digital channels, skills-based routing, APIs, recording, analytics, and workforce engagement management. Amazon Connect: Contact flows, routing profiles, queues, CCP, Contact Lens, Amazon Lex, and AWS Lambda. Salesforce: Service Cloud, CTI integration, Salesforce Voice capabilities, Omni-Channel, and Agentforce. AWS: Lambda, Bedrock, API Gateway, S3, IAM, CloudWatch, EventBridge, and serverless architecture. Telephony: SIP, PSTN, SBC, carrier connectivity, call recording, and voice infrastructure. Integration: REST APIs, webhooks, middleware, event-driven integration, and enterprise application connectivity. Architecture: Cloud-native architecture, HLD/LLD, security, scalability, observability, and HA/DR. Preferred Qualifications Proven experience architecting at least two enterprise-scale contact center implementations. Strong hands-on experience in NICE CXone or Amazon Connect, preferably both platforms. Experience integrating Salesforce Service Cloud with enterprise contact center platforms. Knowledge of GenAI, conversational AI, agentic workflows, and contact center automation. AWS Solutions Architect and/or NICE CXone certifications preferred. Strong client-facing communication, solution estimation, technical leadership, and stakeholder management skills. Mandatory Candidate Screening Criteria Must have independently owned end-to-end contact center solution architecture, not just development or configuration. Must demonstrate deep architectural expertise in NICE CXone or Amazon Connect, with exposure to both preferred. Must have experience with Salesforce Service Cloud / CTI integration. Must have delivered at least two production contact center implementations or migrations. Must be capable of leading architecture discussions, technical estimations, and solution design with enterprise clients.
10/28/2026
Full time
Job Title: Senior / Principal Solution Architect - Contact Center Duration: Long term Job Type: C2C/W2/1099 Location: Remote Primary Skills: NICE CXone, Amazon Connect (AWS), Siera Role Overview We are looking for an experienced End-to-End Contact Center Solution Architect with deep expertise in NICE CXone, Siera and Amazon Connect to lead enterprise contact center transformation initiatives. The architect will be responsible for solution discovery, architecture, design, integration, implementation, migration, and deployment of cloud-based omnichannel contact center platforms. The ideal candidate must have strong hands-on architecture experience, particularly integrating contact center platforms with Salesforce Service Cloud, enterprise applications, and AI-powered customer service solutions. Hiring Preference: Candidates with expertise across NICE CXone, Siera, Amazon Connect, Salesforce Service Cloud, and AI-enabled contact center transformation will be prioritized. Key Responsibilities Own end-to-end solution architecture for NICE CXone and Amazon Connect implementations, modernization, and migration programs. Design enterprise contact center capabilities, including IVR, ACD, CTI, omnichannel routing, inbound/outbound calling, and digital engagement. Architect Salesforce Service Cloud integrations, including agent desktop, screen pops, customer 360, case management, and workflow automation. Design conversational AI, virtual agents, intelligent routing, agent assist, real-time transcription, call summarization, and sentiment analysis solutions. Define integration architecture using AWS Lambda, Lex, Bedrock, API Gateway, REST APIs, and event-driven services. Lead legacy contact center migrations, telephony integrations, data migration, testing, cutover, and production deployment. Develop high-level and low-level architecture, integration specifications, solution estimates, and implementation roadmaps. Ensure security, scalability, high availability, disaster recovery, performance, and regulatory compliance. Provide technical leadership to engineering teams and collaborate with business stakeholders, enterprise architects, and client leadership. Required Technical Skills NICE CXone / Siera: ACD, Studio, IVR, digital channels, skills-based routing, APIs, recording, analytics, and workforce engagement management. Amazon Connect: Contact flows, routing profiles, queues, CCP, Contact Lens, Amazon Lex, and AWS Lambda. Salesforce: Service Cloud, CTI integration, Salesforce Voice capabilities, Omni-Channel, and Agentforce. AWS: Lambda, Bedrock, API Gateway, S3, IAM, CloudWatch, EventBridge, and serverless architecture. Telephony: SIP, PSTN, SBC, carrier connectivity, call recording, and voice infrastructure. Integration: REST APIs, webhooks, middleware, event-driven integration, and enterprise application connectivity. Architecture: Cloud-native architecture, HLD/LLD, security, scalability, observability, and HA/DR. Preferred Qualifications Proven experience architecting at least two enterprise-scale contact center implementations. Strong hands-on experience in NICE CXone or Amazon Connect, preferably both platforms. Experience integrating Salesforce Service Cloud with enterprise contact center platforms. Knowledge of GenAI, conversational AI, agentic workflows, and contact center automation. AWS Solutions Architect and/or NICE CXone certifications preferred. Strong client-facing communication, solution estimation, technical leadership, and stakeholder management skills. Mandatory Candidate Screening Criteria Must have independently owned end-to-end contact center solution architecture, not just development or configuration. Must demonstrate deep architectural expertise in NICE CXone or Amazon Connect, with exposure to both preferred. Must have experience with Salesforce Service Cloud / CTI integration. Must have delivered at least two production contact center implementations or migrations. Must be capable of leading architecture discussions, technical estimations, and solution design with enterprise clients.
Credit Acceptance Corporation
San Francisco, California
At Credit Acceptance, we are building on the foundation of a successful business while investing in the future through technology, data, AI, and continuous improvement. As we continue to evolve, our Team Members play an active role in improving experiences, driving meaningful change, and shaping the future of our business. We foster an environment where people are empowered to contribute ideas, develop their careers, make an impact, and help lead our continued transformation. Our Engineering teams are helping shape the future of Credit Acceptance through innovation. Team Members collaborate across the organization to solve complex challenges, build impactful solutions, challenge the status quo, and support informed business decisions. We value curiosity, continuous learning, and new ideas from people who are passionate about driving modernization and meaningful business impact. Outcomes and Activities Enterprise target architecture: Convene the principal and staff engineers who own each domain to define the end-state architecture across originations, servicing, marketplace, data, and AI, and use it to drive the multi-year plan. Ensure every component has a defined interface with stated inputs and outputs, every unmade decision has a written principle standing in for it, and the document states honestly how close the organization is to the end state. Publish the architecture, including the tradeoffs that were rejected and why. Agentic AI architecture across the enterprise: Own the enterprise agent architecture spanning servicing and collections, the dealer side, originations, and internal engineering and back-office workflows, built on one common foundation rather than one stack per team. Establish a governed way for agents to discover and call business capabilities, data, and tools, using the Model Context Protocol as the integration layer. Define an identity and authorization model that treats an agent as a first-class actor with its own least-privilege entitlements, along with observability, evaluation, and cost controls that work consistently for every agent. Set policy on what an agent may decide independently versus what stays with a person, and define where that line moves and on what evidence. Design the architecture to produce an examiner-ready record of what each agent saw, recommended, and touched, and set the evaluation and adversarial testing approach that makes agent outcomes defensible. Ensure the same foundation and controls apply to agents built by outside firms on the company's behalf. Migration off on-premises infrastructure: Own the technical strategy for migrating transactional and analytical workloads off on-premises infrastructure to the company's strategic targets - AWS for transactional workloads and Databricks for analytical workloads - determining what lifts and shifts, what replatforms, what gets re-architected on the way versus after, and what the steady-state cost looks like. Own the resilience and recovery architecture for the target state. Data platform architecture: Set the architecture for change-data-capture-based ingestion, streaming where warranted, and a modern warehouse with no job-scheduling dependency, moving the organization from largely batch analytical data movement to real time. Help settle the open question of who owns the transactional and analytical data models. Real-time decisioning, model serving, and experimentation: Architect for pricing and credit model and scorecard updates that drop in as a layer rather than requiring a multi-quarter rebuild, and for an experimentation platform that supports orders of magnitude more concurrent experiments than a conventional release process allows. Marketplace and search architecture: Own the architecture and interfaces for a unified vehicle inventory, consumer search, and lead routing platform, ensuring the data model supports more than one class of seller from the start. AI-native engineering practice: Define the golden path for how software is specified, generated, reviewed, tested, and deployed, including the analyzers and gates that enforce it, and measure the inputs to that practice rather than just the outputs. Hold the build-versus-buy bar for AI capability, building what is core competency and about to scale, and renting the rest. Performance and peak readiness: Own the instrumentation, baseline, and remediation architecture needed to meet the standard that no page takes more than one second. Own peak-event headroom, including understanding the limits of each system and maintaining tested degradation levers ahead of need. Operating approach: Move the organization from project-shaped systems toward owned platforms with stated contracts. Document every component's inputs and outputs, and be ready to argue why closely coupled components should not be consolidated into one. Work toward a two-week requirement-to-production iteration bar, treating architecture that cannot be delivered incrementally as unfinished. Name what comes off the plan whenever a change in direction is requested. Make the call and own the outcome on architectural recommendations. Treat security, privacy, auditability, and regulatory obligation as design inputs from the start in this regulated environment. Hands-on, not hands-off: This is not optional. Stay personally engaged in the technical work rather than directing it from a distance. Join design reviews, write proofs of concept, read code, and engage in incident analysis. This hands-on time does not replace the work the teams own, and it is not a fallback when delivery slips. Every engineer in the organization will read how you write, how you argue a design, how you handle being wrong, and how you treat engineers who disagree with you as the bar. Staff and principal engineers should be measurably better at this work for having worked with you. Success measures: A published target architecture the domain owners agree with and that the annual and long-range plans are actually written against; an enterprise agent foundation that internal teams and partners build on, with access controls, evaluation, and audit records in place; a credible, dated, costed migration path off on-premises infrastructure and demonstrated progress against it; measured improvement in chosen input metrics such as latency, availability, recovery objectives, deployment frequency, and experiment throughput; growth in the number of principal and staff engineers who are better at this work as a result of this role; and architectural decisions that stop being relitigated because the reasoning was written down and the interfaces were clear. Competencies Customer Empathy: Customer Empathy is the ability to understand the perspectives, pain points, and experiences of customers. It involves actively putting oneself in the customer's shoes, comprehending their needs and challenges, and using that understanding to provide a better, more customer-centric experience. Engineering Excellence: Engineering Excellence is about bringing great craftsmanship and thought leadership to deliver an outstanding product that delights customers and solves for the business. This involves the pursuit and achievement of high standards, best practices, innovation, and superior solutions. One Team: A One Team mindset refers to a collaborative approach across the organization, where individuals work together seamlessly, without boundaries, as a single, cohesive team. Shared goals, open communication and mutual support create a sense of collective purpose. This enables teams to navigate challenges and pursue shared objectives more effectively. Owner's Mindset: Owner's Mindset involves adopting a set of behaviors that reflect a sense of responsibility, accountability, strategic thinking, and a proactive approach to managing your domain. As an owner, you understand the business and your domain(s) deeply and solve for the right outcome for the domain(s) and the business. Requirements Bachelor's degree in Computer Science, Information Systems, or closely related field of study; or equivalent work experience Minimum 10 years of software engineering experience or comparable depth of experience A track record of setting and delivering multi-year technical strategy at enterprise scale, as an individual contributor rather than through a reporting line. Depth in distributed systems architecture, and in at least two of: agentic or LLM-based systems in production; large-scale cloud migration of transactional systems; modern data platform and lakehouse architecture; machine learning platform and model serving; high-traffic consumer or marketplace applications. Architecture ownership of agentic or LLM-based systems that reached production, including how tool and data access were governed, how the system was evaluated, and what its failure modes turned out to be. Demonstrated ownership of a legacy-to-modern migration of systems the business runs on, including the sequencing, the cost case, and the failure modes, with production revenue at stake rather than only familiarity with the concept. Hands-on credibility today: actively reads code, writes proofs of concept, joins design reviews, and participates in incident analysis. Evidence of influence without authority across organizational boundaries, including work that changed direction at the executive level. Strong written communication; architecture here is carried by documents that other people can act on without the author in the room. Demonstrated ability to develop staff and principal engineers, and to raise the technical bar of engineers not directly managed. Experience delivering in a regulated industry, or a clear ability to work inside audit, security, and compliance constraints without treating them as an obstacle. Candidates must reside in or be willing to relocate to one of the following hub locations: the greater Southfield, Michigan . click apply for full job details
10/28/2026
Full time
At Credit Acceptance, we are building on the foundation of a successful business while investing in the future through technology, data, AI, and continuous improvement. As we continue to evolve, our Team Members play an active role in improving experiences, driving meaningful change, and shaping the future of our business. We foster an environment where people are empowered to contribute ideas, develop their careers, make an impact, and help lead our continued transformation. Our Engineering teams are helping shape the future of Credit Acceptance through innovation. Team Members collaborate across the organization to solve complex challenges, build impactful solutions, challenge the status quo, and support informed business decisions. We value curiosity, continuous learning, and new ideas from people who are passionate about driving modernization and meaningful business impact. Outcomes and Activities Enterprise target architecture: Convene the principal and staff engineers who own each domain to define the end-state architecture across originations, servicing, marketplace, data, and AI, and use it to drive the multi-year plan. Ensure every component has a defined interface with stated inputs and outputs, every unmade decision has a written principle standing in for it, and the document states honestly how close the organization is to the end state. Publish the architecture, including the tradeoffs that were rejected and why. Agentic AI architecture across the enterprise: Own the enterprise agent architecture spanning servicing and collections, the dealer side, originations, and internal engineering and back-office workflows, built on one common foundation rather than one stack per team. Establish a governed way for agents to discover and call business capabilities, data, and tools, using the Model Context Protocol as the integration layer. Define an identity and authorization model that treats an agent as a first-class actor with its own least-privilege entitlements, along with observability, evaluation, and cost controls that work consistently for every agent. Set policy on what an agent may decide independently versus what stays with a person, and define where that line moves and on what evidence. Design the architecture to produce an examiner-ready record of what each agent saw, recommended, and touched, and set the evaluation and adversarial testing approach that makes agent outcomes defensible. Ensure the same foundation and controls apply to agents built by outside firms on the company's behalf. Migration off on-premises infrastructure: Own the technical strategy for migrating transactional and analytical workloads off on-premises infrastructure to the company's strategic targets - AWS for transactional workloads and Databricks for analytical workloads - determining what lifts and shifts, what replatforms, what gets re-architected on the way versus after, and what the steady-state cost looks like. Own the resilience and recovery architecture for the target state. Data platform architecture: Set the architecture for change-data-capture-based ingestion, streaming where warranted, and a modern warehouse with no job-scheduling dependency, moving the organization from largely batch analytical data movement to real time. Help settle the open question of who owns the transactional and analytical data models. Real-time decisioning, model serving, and experimentation: Architect for pricing and credit model and scorecard updates that drop in as a layer rather than requiring a multi-quarter rebuild, and for an experimentation platform that supports orders of magnitude more concurrent experiments than a conventional release process allows. Marketplace and search architecture: Own the architecture and interfaces for a unified vehicle inventory, consumer search, and lead routing platform, ensuring the data model supports more than one class of seller from the start. AI-native engineering practice: Define the golden path for how software is specified, generated, reviewed, tested, and deployed, including the analyzers and gates that enforce it, and measure the inputs to that practice rather than just the outputs. Hold the build-versus-buy bar for AI capability, building what is core competency and about to scale, and renting the rest. Performance and peak readiness: Own the instrumentation, baseline, and remediation architecture needed to meet the standard that no page takes more than one second. Own peak-event headroom, including understanding the limits of each system and maintaining tested degradation levers ahead of need. Operating approach: Move the organization from project-shaped systems toward owned platforms with stated contracts. Document every component's inputs and outputs, and be ready to argue why closely coupled components should not be consolidated into one. Work toward a two-week requirement-to-production iteration bar, treating architecture that cannot be delivered incrementally as unfinished. Name what comes off the plan whenever a change in direction is requested. Make the call and own the outcome on architectural recommendations. Treat security, privacy, auditability, and regulatory obligation as design inputs from the start in this regulated environment. Hands-on, not hands-off: This is not optional. Stay personally engaged in the technical work rather than directing it from a distance. Join design reviews, write proofs of concept, read code, and engage in incident analysis. This hands-on time does not replace the work the teams own, and it is not a fallback when delivery slips. Every engineer in the organization will read how you write, how you argue a design, how you handle being wrong, and how you treat engineers who disagree with you as the bar. Staff and principal engineers should be measurably better at this work for having worked with you. Success measures: A published target architecture the domain owners agree with and that the annual and long-range plans are actually written against; an enterprise agent foundation that internal teams and partners build on, with access controls, evaluation, and audit records in place; a credible, dated, costed migration path off on-premises infrastructure and demonstrated progress against it; measured improvement in chosen input metrics such as latency, availability, recovery objectives, deployment frequency, and experiment throughput; growth in the number of principal and staff engineers who are better at this work as a result of this role; and architectural decisions that stop being relitigated because the reasoning was written down and the interfaces were clear. Competencies Customer Empathy: Customer Empathy is the ability to understand the perspectives, pain points, and experiences of customers. It involves actively putting oneself in the customer's shoes, comprehending their needs and challenges, and using that understanding to provide a better, more customer-centric experience. Engineering Excellence: Engineering Excellence is about bringing great craftsmanship and thought leadership to deliver an outstanding product that delights customers and solves for the business. This involves the pursuit and achievement of high standards, best practices, innovation, and superior solutions. One Team: A One Team mindset refers to a collaborative approach across the organization, where individuals work together seamlessly, without boundaries, as a single, cohesive team. Shared goals, open communication and mutual support create a sense of collective purpose. This enables teams to navigate challenges and pursue shared objectives more effectively. Owner's Mindset: Owner's Mindset involves adopting a set of behaviors that reflect a sense of responsibility, accountability, strategic thinking, and a proactive approach to managing your domain. As an owner, you understand the business and your domain(s) deeply and solve for the right outcome for the domain(s) and the business. Requirements Bachelor's degree in Computer Science, Information Systems, or closely related field of study; or equivalent work experience Minimum 10 years of software engineering experience or comparable depth of experience A track record of setting and delivering multi-year technical strategy at enterprise scale, as an individual contributor rather than through a reporting line. Depth in distributed systems architecture, and in at least two of: agentic or LLM-based systems in production; large-scale cloud migration of transactional systems; modern data platform and lakehouse architecture; machine learning platform and model serving; high-traffic consumer or marketplace applications. Architecture ownership of agentic or LLM-based systems that reached production, including how tool and data access were governed, how the system was evaluated, and what its failure modes turned out to be. Demonstrated ownership of a legacy-to-modern migration of systems the business runs on, including the sequencing, the cost case, and the failure modes, with production revenue at stake rather than only familiarity with the concept. Hands-on credibility today: actively reads code, writes proofs of concept, joins design reviews, and participates in incident analysis. Evidence of influence without authority across organizational boundaries, including work that changed direction at the executive level. Strong written communication; architecture here is carried by documents that other people can act on without the author in the room. Demonstrated ability to develop staff and principal engineers, and to raise the technical bar of engineers not directly managed. Experience delivering in a regulated industry, or a clear ability to work inside audit, security, and compliance constraints without treating them as an obstacle. Candidates must reside in or be willing to relocate to one of the following hub locations: the greater Southfield, Michigan . click apply for full job details
About Arcticom Offering a broad range of information technology solutions, Arcticom, LLC provides network and systems administration, enterprise architecture and resource planning, certification and accreditation, software design, programming, maintenance of telecommunications and land mobile radio equipment and systems, help desk support and IT transformation services among other services. Arcticom offers impressive performance that is routinely recognized with exceptional ratings and commendations tied to installation successes. Satisfied Bering Straits Native Corporation (BSNC) family customers include the U.S. Air Force, Army, Navy, Coast Guard, the Departments of State, Justice, Commerce, Agriculture, Interior, Homeland Security, the General Services Administration, the Defense Logistics Agency and the U.S Census Bureau. About this position: Public Member Consultant in Washington, DC The Essential Duties and Responsibilities are intended to present a descriptive list of the range of duties performed for this position and are not intended to reflect all duties performed within the job. Other duties may be assigned. To perform this job successfully, an individual must be able to satisfactorily perform each essential duty. The requirements listed below are representative of the knowledge, skill and/or ability required. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions of the position. Arcticom, a company within the BSNC family, is currently seeking a Public Member Consultant career professional to support The Department of State, Office of Performance Evaluation in performing annual reviews of Foreign Service personnel. This position requires an individual with experience in one of the following career areas: Information Technology, Law Enforcement, Educators (at all levels), Medical Practitioners, Business, Human Resources, Building Operations, Transportation and Freight, Security Engineer, Media, or Finance Professionals. This effort requires availability of 40 hours per week (minimum) from mid-May to the mid-August and some part-time consulting from September thru April. However, two weeks of board training must be in-person in Wash DC where all members meet the Foreign Service members you may be assigned to work with during the summer cycle. After the training period, the summer board cycle will continue full-time virtually. Travel costs are reimbursed if outside the DMV area, according to standard government rates. The basic requirements include being a US Citizen with a college degree that can pass a background check (an unclassified security clearance) without any a legal or financial conflict of interest and has traveled or worked/lived abroad. Background: The Department of State maintains a rigorous system to promote employees (worldwide) on an annual basis as required under the Foreign Service Act of 1980. One key requirement is to include (1) Public Member consultant on each of the multiple Foreign Service Selection Boards that review performance records of Foreign Service personnel; recommend employees for promotion; and recommend other personnel actions when warranted. Each board will consist of 4 Department of State professionals and 1 Public Member. Public members bring diverse experience and perspectives to Board deliberations that enhance the integrity of the performance review process for employees who represent the United States. Essential Duties & Responsibilities The Department of State, Office of Performance Evaluation Boards, can meet from four to nine weeks. The projected time frame for concentrated board activity is approximately mid-May to mid-August, each year. Selected individuals must be available and online during core business hours of 8:00 AM to 5:00 PM or longer, if necessary, which may include weekends and holidays. After this period, there may be other (shorter) boards for which the Arcticom Program Manager would recall interested individuals for additional board assignments. Such boards could include but are not limited to: Department Senior Review Board, the Interagency Review Board, Performance Pay Board, and Reconstituted Boards to review a limited number of personnel files. The first 2 weeks of on-site training will occur at U.S Department of State, SA- G St NW, Washington, DC 20520 or other local government buildings. The remainder of the board record reviews will be performed remotely. Required (Minimum Necessary) Qualifications Education Requirements: Bachelor's degree Have overseas experience, which can be through work, education, or personal travel. Be available to serve on a full-time basis during the entire time that the boards are in session. Not be employed in the Federal service at the time of appointment or during his or her service on a Selection Board. Not be a registered agent of a foreign principal, a lobbyist for a foreign entity, or receive income from a government of a foreign country. Not be a retiree from State, USAID, Foreign Commercial Service, Foreign Agriculture Service, or USGMA. Not be a friend, relative or other personal contact of any person employed in the Global Talent Management Office of Performance Evaluation (GTM/PE), the Office of the Director General and the Director of Global Talent (DGTM), or any office or individual involved in the selection/formalization of the service of the public member. Not be a direct recipient of grants or other funding from the Department of State such that it could be deemed a conflict of interest. Prior Experience: Public Member Consultant candidates experience including but not limited to: Information Technology, Law Enforcement, Educators (all levels), Medical Practitioners, Business, Human Resources, Building Operations, Transportation and Freight, Security Engineer, Media, or Finance Professionals. Required: US Citizen, Overseas travel or work, pass a background check, and accept up to a one-year consultant assignment. (please list countries of international travel and interest in International Affairs on resume) Knowledge, Skills, Abilities, and Other Characteristics Knowledge of organizational procedures and workflows - understanding how work moves through a company. Basic knowledge of relevant technologies or tools - e.g., Microsoft 365, communication platforms, or industry standard software. Knowledge of customer service practices - principles of providing quality service and managing inquiries professionally. Knowledge of data privacy and confidentiality principles - awareness of proper handling of sensitive information. Communication skills (written and verbal) - ability to convey information clearly and professionally. Time management and prioritization - balancing multiple tasks and meeting deadlines. Problem solving and critical thinking - analyzing issues and selecting appropriate solutions. Interpersonal and teamwork skills - building rapport and collaborating effectively with others. Attention to detail - producing accurate, error free work. Preferred N/A Necessary Physical Requirements The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this role. Employees must always maintain a constant state of mental alertness. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. Essential and marginal functions may require maintaining the physical condition necessary for bending, stooping, sitting, walking, or standing for prolonged periods of time; most of the time is spent sitting in a comfortable position with frequent opportunities to move about. Work Environment The work environmental characteristics described here are representative of those that must be borne by an employee to successfully perform the essential functions of the role. Employees must always maintain a constant state of situational awareness. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. Job is performed in an office setting with exposure to computer screens and requires extensive use of a computer, keyboard, mouse, and multi-line telephone system. The work described herein is primarily a modern office setting. Occasional travel may be required. Supervisory Responsibilities This position will not have supervisory responsibilities. DOT Covered/Safety-Sensitive Role Requirements This position is not subject to federal requirements regarding Department of Transportation "safety-sensitive" functions. Additional Qualifying Factors As a condition of employment, you will be required to pass a pre-employment drug screening and have acceptable background check results. If applicable to the contract, you must also obtain and maintain the appropriate clearance levels required and must also be able to obtain access to military installations. Shareholder Preference BSNC gives hiring, promotion, training, and retention preference to BSNC shareholders, shareholder descendants and shareholder spouses who meet the minimum qualifications for the job. Bering Straits Native Corporation is an equal opportunity employer. All applicants will receive consideration for employment without regard to any status protected by state or federal law, or any other basis prohibited by law.
10/28/2026
Full time
About Arcticom Offering a broad range of information technology solutions, Arcticom, LLC provides network and systems administration, enterprise architecture and resource planning, certification and accreditation, software design, programming, maintenance of telecommunications and land mobile radio equipment and systems, help desk support and IT transformation services among other services. Arcticom offers impressive performance that is routinely recognized with exceptional ratings and commendations tied to installation successes. Satisfied Bering Straits Native Corporation (BSNC) family customers include the U.S. Air Force, Army, Navy, Coast Guard, the Departments of State, Justice, Commerce, Agriculture, Interior, Homeland Security, the General Services Administration, the Defense Logistics Agency and the U.S Census Bureau. About this position: Public Member Consultant in Washington, DC The Essential Duties and Responsibilities are intended to present a descriptive list of the range of duties performed for this position and are not intended to reflect all duties performed within the job. Other duties may be assigned. To perform this job successfully, an individual must be able to satisfactorily perform each essential duty. The requirements listed below are representative of the knowledge, skill and/or ability required. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions of the position. Arcticom, a company within the BSNC family, is currently seeking a Public Member Consultant career professional to support The Department of State, Office of Performance Evaluation in performing annual reviews of Foreign Service personnel. This position requires an individual with experience in one of the following career areas: Information Technology, Law Enforcement, Educators (at all levels), Medical Practitioners, Business, Human Resources, Building Operations, Transportation and Freight, Security Engineer, Media, or Finance Professionals. This effort requires availability of 40 hours per week (minimum) from mid-May to the mid-August and some part-time consulting from September thru April. However, two weeks of board training must be in-person in Wash DC where all members meet the Foreign Service members you may be assigned to work with during the summer cycle. After the training period, the summer board cycle will continue full-time virtually. Travel costs are reimbursed if outside the DMV area, according to standard government rates. The basic requirements include being a US Citizen with a college degree that can pass a background check (an unclassified security clearance) without any a legal or financial conflict of interest and has traveled or worked/lived abroad. Background: The Department of State maintains a rigorous system to promote employees (worldwide) on an annual basis as required under the Foreign Service Act of 1980. One key requirement is to include (1) Public Member consultant on each of the multiple Foreign Service Selection Boards that review performance records of Foreign Service personnel; recommend employees for promotion; and recommend other personnel actions when warranted. Each board will consist of 4 Department of State professionals and 1 Public Member. Public members bring diverse experience and perspectives to Board deliberations that enhance the integrity of the performance review process for employees who represent the United States. Essential Duties & Responsibilities The Department of State, Office of Performance Evaluation Boards, can meet from four to nine weeks. The projected time frame for concentrated board activity is approximately mid-May to mid-August, each year. Selected individuals must be available and online during core business hours of 8:00 AM to 5:00 PM or longer, if necessary, which may include weekends and holidays. After this period, there may be other (shorter) boards for which the Arcticom Program Manager would recall interested individuals for additional board assignments. Such boards could include but are not limited to: Department Senior Review Board, the Interagency Review Board, Performance Pay Board, and Reconstituted Boards to review a limited number of personnel files. The first 2 weeks of on-site training will occur at U.S Department of State, SA- G St NW, Washington, DC 20520 or other local government buildings. The remainder of the board record reviews will be performed remotely. Required (Minimum Necessary) Qualifications Education Requirements: Bachelor's degree Have overseas experience, which can be through work, education, or personal travel. Be available to serve on a full-time basis during the entire time that the boards are in session. Not be employed in the Federal service at the time of appointment or during his or her service on a Selection Board. Not be a registered agent of a foreign principal, a lobbyist for a foreign entity, or receive income from a government of a foreign country. Not be a retiree from State, USAID, Foreign Commercial Service, Foreign Agriculture Service, or USGMA. Not be a friend, relative or other personal contact of any person employed in the Global Talent Management Office of Performance Evaluation (GTM/PE), the Office of the Director General and the Director of Global Talent (DGTM), or any office or individual involved in the selection/formalization of the service of the public member. Not be a direct recipient of grants or other funding from the Department of State such that it could be deemed a conflict of interest. Prior Experience: Public Member Consultant candidates experience including but not limited to: Information Technology, Law Enforcement, Educators (all levels), Medical Practitioners, Business, Human Resources, Building Operations, Transportation and Freight, Security Engineer, Media, or Finance Professionals. Required: US Citizen, Overseas travel or work, pass a background check, and accept up to a one-year consultant assignment. (please list countries of international travel and interest in International Affairs on resume) Knowledge, Skills, Abilities, and Other Characteristics Knowledge of organizational procedures and workflows - understanding how work moves through a company. Basic knowledge of relevant technologies or tools - e.g., Microsoft 365, communication platforms, or industry standard software. Knowledge of customer service practices - principles of providing quality service and managing inquiries professionally. Knowledge of data privacy and confidentiality principles - awareness of proper handling of sensitive information. Communication skills (written and verbal) - ability to convey information clearly and professionally. Time management and prioritization - balancing multiple tasks and meeting deadlines. Problem solving and critical thinking - analyzing issues and selecting appropriate solutions. Interpersonal and teamwork skills - building rapport and collaborating effectively with others. Attention to detail - producing accurate, error free work. Preferred N/A Necessary Physical Requirements The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this role. Employees must always maintain a constant state of mental alertness. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. Essential and marginal functions may require maintaining the physical condition necessary for bending, stooping, sitting, walking, or standing for prolonged periods of time; most of the time is spent sitting in a comfortable position with frequent opportunities to move about. Work Environment The work environmental characteristics described here are representative of those that must be borne by an employee to successfully perform the essential functions of the role. Employees must always maintain a constant state of situational awareness. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. Job is performed in an office setting with exposure to computer screens and requires extensive use of a computer, keyboard, mouse, and multi-line telephone system. The work described herein is primarily a modern office setting. Occasional travel may be required. Supervisory Responsibilities This position will not have supervisory responsibilities. DOT Covered/Safety-Sensitive Role Requirements This position is not subject to federal requirements regarding Department of Transportation "safety-sensitive" functions. Additional Qualifying Factors As a condition of employment, you will be required to pass a pre-employment drug screening and have acceptable background check results. If applicable to the contract, you must also obtain and maintain the appropriate clearance levels required and must also be able to obtain access to military installations. Shareholder Preference BSNC gives hiring, promotion, training, and retention preference to BSNC shareholders, shareholder descendants and shareholder spouses who meet the minimum qualifications for the job. Bering Straits Native Corporation is an equal opportunity employer. All applicants will receive consideration for employment without regard to any status protected by state or federal law, or any other basis prohibited by law.
AI Engineer 4 (MLX, Agentic AI, Gen AI workflows, GraphRAG) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for AI Engineer 4 Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/28/2026
Full time
AI Engineer 4 (MLX, Agentic AI, Gen AI workflows, GraphRAG) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for AI Engineer 4 Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
AI Engineer 4 (MLX, Agentic AI, Gen AI workflows, GraphRAG) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for AI Engineer 4 Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/28/2026
Full time
AI Engineer 4 (MLX, Agentic AI, Gen AI workflows, GraphRAG) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for AI Engineer 4 Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Job Description Job Description The Daily Wire is seeking a Principal Data Engineer to architect and build the systems connecting our subscribers, content, advertising, and digital products. This hands-on role will work across backend services, event-driven pipelines, cloud infrastructure, analytical models, and personalization systems to strengthen our data foundations and support AI-driven content discovery. The ideal candidate brings a strong software engineering background, deep expertise in data-intensive systems, and the ability to influence technical strategy across infrastructure, analytics, and product-facing platforms. Primary Responsibilities Architect and drive the long-term vision for Daily Wire's enterprise data ecosystem, including infrastructure, ingestion, storage, transformation, and real-time analytics. Lead the design and implementation of distributed systems, high-availability APIs, event streams, and real-time data pipelines. Build resilient, production-grade backend services and data workflows using Python or Go and advanced SQL. Design and scale Snowflake data warehouses and layered dbt models that transform complex operational data into reliable data products. Partner with product and analytics leaders to establish event schemas, tracking standards, and unified semantic layers. Architect and operate production machine-learning infrastructure, low-latency inference systems, and feedback loops that power content discovery and personalization. Establish architectural and operational standards for testing, observability, security, reliability, and cost efficiency. Provide technical leadership across AWS cloud infrastructure, containerized services, architecture reviews, code mentorship, and incident response. Experience & Requirements Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience. 10+ years of experience in software engineering, data engineering, analytics infrastructure, or data-intensive platform development. Advanced experience with Snowflake and dbt, including warehouse design, transformation architecture, testing, documentation, data lineage, query optimization, and cost governance. Proven experience building and operating enterprise-grade platforms on AWS, including SageMaker and Personalize. Hands-on experience with infrastructure as code, CI/CD pipelines, system observability, and production operations. Experience with streaming and messaging technologies such as Kafka, Segment, AWS Kinesis, Kinesis Data Firehose, or Apache Flink. Experience building pipelines that support machine-learning model training, serving, recommendation systems, and content personalization. Knowledge of event-time processing, windowing, checkpointing, and schema evolution. Experience creating analytics and reporting solutions using visualization tools such as Tableau. Experience with subscription media, streaming video, content discovery, payments, digital advertising, or high-growth consumer products is preferred. Exceptional problem-solving, debugging, written communication, and cross-functional collaboration skills. To learn more about Daily Wire, please visit the following Daily Wire Facebook and YouTube page links: Daily Wire Daily Wire Facebook Daily Wire YouTube Daily Wire X PragerU Daily Wire provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. Please Note: Daily Wire participates in E-Verify and performs background checks on all new hires. We will provide the Social Security Administration (SSA) and if necessary, the Department of Homeland Security (DHS), with information from each new employee's form I-9 to confirm work authorization. Thank you! CALIFORNIA APPLICANT PRIVACY NOTICE
10/28/2026
Full time
Job Description Job Description The Daily Wire is seeking a Principal Data Engineer to architect and build the systems connecting our subscribers, content, advertising, and digital products. This hands-on role will work across backend services, event-driven pipelines, cloud infrastructure, analytical models, and personalization systems to strengthen our data foundations and support AI-driven content discovery. The ideal candidate brings a strong software engineering background, deep expertise in data-intensive systems, and the ability to influence technical strategy across infrastructure, analytics, and product-facing platforms. Primary Responsibilities Architect and drive the long-term vision for Daily Wire's enterprise data ecosystem, including infrastructure, ingestion, storage, transformation, and real-time analytics. Lead the design and implementation of distributed systems, high-availability APIs, event streams, and real-time data pipelines. Build resilient, production-grade backend services and data workflows using Python or Go and advanced SQL. Design and scale Snowflake data warehouses and layered dbt models that transform complex operational data into reliable data products. Partner with product and analytics leaders to establish event schemas, tracking standards, and unified semantic layers. Architect and operate production machine-learning infrastructure, low-latency inference systems, and feedback loops that power content discovery and personalization. Establish architectural and operational standards for testing, observability, security, reliability, and cost efficiency. Provide technical leadership across AWS cloud infrastructure, containerized services, architecture reviews, code mentorship, and incident response. Experience & Requirements Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience. 10+ years of experience in software engineering, data engineering, analytics infrastructure, or data-intensive platform development. Advanced experience with Snowflake and dbt, including warehouse design, transformation architecture, testing, documentation, data lineage, query optimization, and cost governance. Proven experience building and operating enterprise-grade platforms on AWS, including SageMaker and Personalize. Hands-on experience with infrastructure as code, CI/CD pipelines, system observability, and production operations. Experience with streaming and messaging technologies such as Kafka, Segment, AWS Kinesis, Kinesis Data Firehose, or Apache Flink. Experience building pipelines that support machine-learning model training, serving, recommendation systems, and content personalization. Knowledge of event-time processing, windowing, checkpointing, and schema evolution. Experience creating analytics and reporting solutions using visualization tools such as Tableau. Experience with subscription media, streaming video, content discovery, payments, digital advertising, or high-growth consumer products is preferred. Exceptional problem-solving, debugging, written communication, and cross-functional collaboration skills. To learn more about Daily Wire, please visit the following Daily Wire Facebook and YouTube page links: Daily Wire Daily Wire Facebook Daily Wire YouTube Daily Wire X PragerU Daily Wire provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. Please Note: Daily Wire participates in E-Verify and performs background checks on all new hires. We will provide the Social Security Administration (SSA) and if necessary, the Department of Homeland Security (DHS), with information from each new employee's form I-9 to confirm work authorization. Thank you! CALIFORNIA APPLICANT PRIVACY NOTICE
Job Description Job Description Role : Enterprise Data Architect Location : remote Rate : $80/hr Role Summary The Enterprise Data Architect is responsible for defining and evolving the Commonwealth's enterprise information architecture and reusable data products to support transformation and AI priorities. This role partners with business leaders, product and engineering teams and enterprise technology org to identify which information assets should be shared across agencies and which should remain domain specific. The position will define data domains, create data models, ensure data quality, map source to domain and assist in creating contracts to support modernization initiatives and future AI capabilities. The role serves as the bridge between business processes and technical implementation, ensuring that new solutions contribute to a sustainable enterprise data foundation rather than creating additional silos. The ideal candidate possesses a comprehensive understanding of data architecture principles, practical data modeling experience, and deep expertise in data-centric architecture. Key Responsibilities Enterprise Information Architecture Define conceptual and logical data models for common business entities. Establish canonical models and enterprise information standards. Define relationships between enterprise and domain-specific data assets. Design enterprise information architecture that incorporates data classification, privacy, security, and regulatory requirements by design. Modernization Programs Partner with workflow modernization teams (product and engineering) to embed reusable data products into solution designs. Analyze legacy systems and identify information assets suitable for enterprise reuse. Prevent duplication of data structures across applications and agencies. Support data migration strategies and target-state architecture. Data Product Architecture Identify and support design of reusable data products Define schemas, interfaces, metadata and quality requirements Establish product boundaries, stewardship and ownership models. Data Governance and Metadata Establish data architecture principles, data standards, best practices, and guidelines including data catalog, data lineage, observability, security and interoperability Define business definitions and data quality expectations. Platform and Technology Collaboration Work with engineering and platform teams to translate business concepts into technical designs. Partner with cloud, integration and data teams to implement enterprise data products. Promote API-first and product-based approaches to information sharing. AI Enablement Ensure enterprise data products are discoverable, governed and suitable for future AI use cases. Support semantic layers, knowledge graphs and natural language access to enterprise information. Desired Background and Experience Bachelor of Computer Science, Information Systems, Systems Programming or equivalent combination of relevant education and experience Minimum 10 years of experience in data architecture, information architecture or enterprise architecture. 8 years of hands-on experience in data architecture, data engineering, or advanced database design, modeling experience in designing or implementing data warehouse/data marts, MDM concepts and tools At least 5 years of experience with data platforms such as Snowflake, Databricks, MongoDB and big data on cloud-based ecosystems (AWS, Azure, GCP). Experience working with unstructured data is a plus. Experience working with data security, privacy and regulatory requirements for handling sensitive data Experience in designing and implementing data quality initiatives, including platforms and tooling Demonstrable experience supporting large-scale modernization or digital transformation initiatives across multiple domains and stakeholders Ability to work across domains and stakeholders with strong communication skills Proven ability to develop work plans for self, resolve ambiguity and lead teams without authority Industry Experience in Public sector, Healthcare or Financial Services is preferable Candidates may have previously served as Principal Architect, Enterprise Information Architect, Solution Architect for large enterprises or modernization initiatives Success Measures During the first year, this role will Establish enterprise information architecture principles. Define reusable enterprise data products for priority domains. Support specific modernization initiatives as a model implementation. Introduce metadata and ownership standards. Enable future modernization efforts to reuse common data assets rather than recreating them. Client the foundation for enterprise analytics and AI capabilities across the Commonwealth.
10/28/2026
Full time
Job Description Job Description Role : Enterprise Data Architect Location : remote Rate : $80/hr Role Summary The Enterprise Data Architect is responsible for defining and evolving the Commonwealth's enterprise information architecture and reusable data products to support transformation and AI priorities. This role partners with business leaders, product and engineering teams and enterprise technology org to identify which information assets should be shared across agencies and which should remain domain specific. The position will define data domains, create data models, ensure data quality, map source to domain and assist in creating contracts to support modernization initiatives and future AI capabilities. The role serves as the bridge between business processes and technical implementation, ensuring that new solutions contribute to a sustainable enterprise data foundation rather than creating additional silos. The ideal candidate possesses a comprehensive understanding of data architecture principles, practical data modeling experience, and deep expertise in data-centric architecture. Key Responsibilities Enterprise Information Architecture Define conceptual and logical data models for common business entities. Establish canonical models and enterprise information standards. Define relationships between enterprise and domain-specific data assets. Design enterprise information architecture that incorporates data classification, privacy, security, and regulatory requirements by design. Modernization Programs Partner with workflow modernization teams (product and engineering) to embed reusable data products into solution designs. Analyze legacy systems and identify information assets suitable for enterprise reuse. Prevent duplication of data structures across applications and agencies. Support data migration strategies and target-state architecture. Data Product Architecture Identify and support design of reusable data products Define schemas, interfaces, metadata and quality requirements Establish product boundaries, stewardship and ownership models. Data Governance and Metadata Establish data architecture principles, data standards, best practices, and guidelines including data catalog, data lineage, observability, security and interoperability Define business definitions and data quality expectations. Platform and Technology Collaboration Work with engineering and platform teams to translate business concepts into technical designs. Partner with cloud, integration and data teams to implement enterprise data products. Promote API-first and product-based approaches to information sharing. AI Enablement Ensure enterprise data products are discoverable, governed and suitable for future AI use cases. Support semantic layers, knowledge graphs and natural language access to enterprise information. Desired Background and Experience Bachelor of Computer Science, Information Systems, Systems Programming or equivalent combination of relevant education and experience Minimum 10 years of experience in data architecture, information architecture or enterprise architecture. 8 years of hands-on experience in data architecture, data engineering, or advanced database design, modeling experience in designing or implementing data warehouse/data marts, MDM concepts and tools At least 5 years of experience with data platforms such as Snowflake, Databricks, MongoDB and big data on cloud-based ecosystems (AWS, Azure, GCP). Experience working with unstructured data is a plus. Experience working with data security, privacy and regulatory requirements for handling sensitive data Experience in designing and implementing data quality initiatives, including platforms and tooling Demonstrable experience supporting large-scale modernization or digital transformation initiatives across multiple domains and stakeholders Ability to work across domains and stakeholders with strong communication skills Proven ability to develop work plans for self, resolve ambiguity and lead teams without authority Industry Experience in Public sector, Healthcare or Financial Services is preferable Candidates may have previously served as Principal Architect, Enterprise Information Architect, Solution Architect for large enterprises or modernization initiatives Success Measures During the first year, this role will Establish enterprise information architecture principles. Define reusable enterprise data products for priority domains. Support specific modernization initiatives as a model implementation. Introduce metadata and ownership standards. Enable future modernization efforts to reuse common data assets rather than recreating them. Client the foundation for enterprise analytics and AI capabilities across the Commonwealth.
Job Description Job Description Indent : SF_OP_208618-1 Role : Principal Data Architect Location : Purchase, NY (Hybrid) Rate: $80 to $85/hr Experience : 15 The successful candidate will establish the architectural vision for modernizing data platforms across hybrid cloud and on-premises environments, supporting both high-volume batch processing and low-latency, real-time workloads. This position combines deep hands-on technical expertise with enterprise influence, driving architectural decisions that maximize the value of Client data assets while meeting the highest standards for security, resiliency, compliance, and operational excellence. Role: • Serve as the senior technical leader for enterprise data architecture, partnering closely with the VP and senior technology leadership. • Act as a trusted advisor to executive stakeholders, translating business strategy into scalable, secure, and resilient data architecture decisions. • Define and evolve Client's global data architecture strategy across hybrid cloud and on-premises environments. • Architect secure, resilient solutions that meet global regulatory and compliance mandates, including GDPR, ISO 20022, and regional data localization requirements. • Champion Data Mesh principles, enabling data-as-a-product capabilities, federated ownership, governance, and self-service access. • Establish and drive enterprise architecture standards, design patterns, and engineering best practices through the Data & Analytics Architecture Review Board. • Lead the modernization of legacy data platforms to cloud native architectures across AWS, Azure, and GCP. • Drive adoption of modern data technologies, including Databricks, Snowflake, Delta Lake, and streaming platforms. • Enable both real time and batch analytics use cases to support high availability, mission critical workloads. • Evaluate and incorporate emerging technologies, including AI-enabled data platforms and agent-based architectures. • Mentor and influence global engineering teams, fostering a culture of technical excellence, accountability, and thoughtful risk taking. All About You: • Proven experience as a Principal Engineer, Lead Architect, or equivalent technical leadership role driving enterprise-scale data architecture and platform strategy. • Deep expertise designing, building, and operating distributed data systems at global scale. • Strong hands-on experience with technologies such as Apache Spark, Kafka, Flink, NiFi, Databricks, Snowflake, and modern cloud-native data platforms. • Demonstrated success modernizing data platforms using cloud native architectures across AWS, Azure, and/or GCP. • Experience integrating AI driven capabilities into data platforms, with appropriate governance and guardrails for emerging use cases, including agentic commerce. • Strong understanding of data governance, security, and regulatory compliance in highly regulated, global environments. • Proven ability to lead and influence architectural initiatives within Agile, SAFe, or product centric delivery models, partnering effectively with product, engineering, and business stakeholders. • Demonstrated ability to influence technical and business decisions at all levels, including C-suite stakeholders. • Strong executive presence with the ability to translate complex architecture concepts into business language. • Exceptional communication skills, with the ability to articulate complex technical concepts to executive and non-technical audiences. • Strong Decency Quotient (DQ) with a track record of building inclusive, collaborative, high performing teams. • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field, or equivalent practical experience.
10/28/2026
Full time
Job Description Job Description Indent : SF_OP_208618-1 Role : Principal Data Architect Location : Purchase, NY (Hybrid) Rate: $80 to $85/hr Experience : 15 The successful candidate will establish the architectural vision for modernizing data platforms across hybrid cloud and on-premises environments, supporting both high-volume batch processing and low-latency, real-time workloads. This position combines deep hands-on technical expertise with enterprise influence, driving architectural decisions that maximize the value of Client data assets while meeting the highest standards for security, resiliency, compliance, and operational excellence. Role: • Serve as the senior technical leader for enterprise data architecture, partnering closely with the VP and senior technology leadership. • Act as a trusted advisor to executive stakeholders, translating business strategy into scalable, secure, and resilient data architecture decisions. • Define and evolve Client's global data architecture strategy across hybrid cloud and on-premises environments. • Architect secure, resilient solutions that meet global regulatory and compliance mandates, including GDPR, ISO 20022, and regional data localization requirements. • Champion Data Mesh principles, enabling data-as-a-product capabilities, federated ownership, governance, and self-service access. • Establish and drive enterprise architecture standards, design patterns, and engineering best practices through the Data & Analytics Architecture Review Board. • Lead the modernization of legacy data platforms to cloud native architectures across AWS, Azure, and GCP. • Drive adoption of modern data technologies, including Databricks, Snowflake, Delta Lake, and streaming platforms. • Enable both real time and batch analytics use cases to support high availability, mission critical workloads. • Evaluate and incorporate emerging technologies, including AI-enabled data platforms and agent-based architectures. • Mentor and influence global engineering teams, fostering a culture of technical excellence, accountability, and thoughtful risk taking. All About You: • Proven experience as a Principal Engineer, Lead Architect, or equivalent technical leadership role driving enterprise-scale data architecture and platform strategy. • Deep expertise designing, building, and operating distributed data systems at global scale. • Strong hands-on experience with technologies such as Apache Spark, Kafka, Flink, NiFi, Databricks, Snowflake, and modern cloud-native data platforms. • Demonstrated success modernizing data platforms using cloud native architectures across AWS, Azure, and/or GCP. • Experience integrating AI driven capabilities into data platforms, with appropriate governance and guardrails for emerging use cases, including agentic commerce. • Strong understanding of data governance, security, and regulatory compliance in highly regulated, global environments. • Proven ability to lead and influence architectural initiatives within Agile, SAFe, or product centric delivery models, partnering effectively with product, engineering, and business stakeholders. • Demonstrated ability to influence technical and business decisions at all levels, including C-suite stakeholders. • Strong executive presence with the ability to translate complex architecture concepts into business language. • Exceptional communication skills, with the ability to articulate complex technical concepts to executive and non-technical audiences. • Strong Decency Quotient (DQ) with a track record of building inclusive, collaborative, high performing teams. • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field, or equivalent practical experience.
Job Description Job Description Tesorio is the cash flow performance platform, which Accounts Receivable, Treasury, and FP&A teams use to manage, predict, and collect cash. Its AI processes over $30 billion in transactions each year for companies ranging from 50 to 10,000 employees. Series A company Founded: 2013 Funding: $16.9M Visa: Will transfer H1 Salary: $0 - $200k Job required skills: Cloud, NoSQL, SQL, SaaS, Python, Django Responsibilities Responsible for designing & implementing data architecture that will help with scalability, performance & reliability. You will own the data architecture at our company and work closely with the CTO & Engineering Leadership in order to solve the toughest technical challenges You will be a key member of the Engineering Leadership and help set the technical direction at our company Provide coaching & mentorship across the entire engineering organization Architect & implement production-grade code that is reliable, maintainable & scalable Anticipate technical challenges that we will face as we scale About you You've previously worked at startups and have helped them scale You're excited to lead data architecture at a startup You like to design & architect solutions that are reliable, maintainable & scalable You enjoy writing production-grade code to help implement your solutions You have strong opinions, but you hold them loosely You're always learning You love building and shipping magical products that will help thousands of companies The Ideal Candidate 10+ years of experience as a software engineer Prior experience as a Staff Software Engineer or a more senior engineering role Expert at data architecture. From schema design, data storage technologies, debugging data problems, building scalable data solutions & more. You're intimately familiar with the technology problems startups face as they scale because you've worked at a startup before and helped them scale Experience working on large multi-tenant SaaS systems Expertise working on cloud platforms (e.g. AWS) and building large-scale data architectures leveraging their technologies Nice to have Expertise with Python & Python web frameworks (e.g. Django, Flask) Experience working with financial data or working at a fintech company Expertise with AWS
10/28/2026
Full time
Job Description Job Description Tesorio is the cash flow performance platform, which Accounts Receivable, Treasury, and FP&A teams use to manage, predict, and collect cash. Its AI processes over $30 billion in transactions each year for companies ranging from 50 to 10,000 employees. Series A company Founded: 2013 Funding: $16.9M Visa: Will transfer H1 Salary: $0 - $200k Job required skills: Cloud, NoSQL, SQL, SaaS, Python, Django Responsibilities Responsible for designing & implementing data architecture that will help with scalability, performance & reliability. You will own the data architecture at our company and work closely with the CTO & Engineering Leadership in order to solve the toughest technical challenges You will be a key member of the Engineering Leadership and help set the technical direction at our company Provide coaching & mentorship across the entire engineering organization Architect & implement production-grade code that is reliable, maintainable & scalable Anticipate technical challenges that we will face as we scale About you You've previously worked at startups and have helped them scale You're excited to lead data architecture at a startup You like to design & architect solutions that are reliable, maintainable & scalable You enjoy writing production-grade code to help implement your solutions You have strong opinions, but you hold them loosely You're always learning You love building and shipping magical products that will help thousands of companies The Ideal Candidate 10+ years of experience as a software engineer Prior experience as a Staff Software Engineer or a more senior engineering role Expert at data architecture. From schema design, data storage technologies, debugging data problems, building scalable data solutions & more. You're intimately familiar with the technology problems startups face as they scale because you've worked at a startup before and helped them scale Experience working on large multi-tenant SaaS systems Expertise working on cloud platforms (e.g. AWS) and building large-scale data architectures leveraging their technologies Nice to have Expertise with Python & Python web frameworks (e.g. Django, Flask) Experience working with financial data or working at a fintech company Expertise with AWS
Job Description Job Description Interviews: two internal rounds, one customer Experience: Minimum 12 years Job Description: About the Role We are looking for a Principal AI & Data Architect to define and lead our enterprise data and AI architecture. You will design a Snowflake-centric data platform with a strong semantic layer, and build the foundations for agentic AI systems that reason over trusted, governed enterprise data. You will be a hands-on technical leader, partnering with business, engineering, and security teams to turn data into reliable, AI-ready products. Key Responsibilities Data Architecture & Snowflake Platform Own the end-to-end architecture of the Snowflake Data Cloud: ingestion, storage, transformation, serving, and consumption. Design scalable, cost-efficient solutions using Snowflake features such as Snowpipe, Streams & Tasks, Dynamic Tables, Snowpark, Iceberg tables, Secure Data Sharing, and Marketplace. Define standards for performance tuning, warehouse sizing, clustering, and FinOps/cost governance. Lead modernization and migration from legacy platforms (Teradata, Oracle, Hadoop, SQL Server) to Snowflake. Semantic & Data Modeling Architect enterprise semantic layers, including business metrics, dimensions, hierarchies, and entity relationships. Design dimensional (Kimball), Data Vault 2.0, and canonical/domain models, and map them to the semantic layer. Implement Snowflake Semantic Views and Cortex Analyst semantic models, and integrate with tools like dbt Semantic Layer/MetricFlow, AtScale, Cube, or LookML. Establish ontologies, knowledge graphs, and business glossaries to ensure consistent meaning across the enterprise. Own metadata, lineage, and data contracts across domains (data mesh / data product approach). Agentic AI & GenAI Architecture Design agentic AI architectures: multi-agent orchestration, tool use, planning, memory, and guardrails. Build solutions on Snowflake Cortex (Cortex Agents, Cortex Analyst, Cortex Search, AI functions) and integrate with LLMs and frameworks such as LangGraph, LangChain, LlamaIndex, AutoGen, or CrewAI. Implement RAG and text-to-SQL patterns grounded in the semantic layer for accurate, explainable answers. Leverage MCP (Model Context Protocol) and API/tool integrations to expose governed data and actions to agents. Define LLMOps/AgentOps practices: evaluation, observability, prompt/version management, human-in-the-loop, and cost control. Establish Responsible AI practices covering bias, hallucination, privacy, and auditability. Governance, Security & Leadership Implement RBAC, row/column-level security, dynamic masking, tagging, and compliance controls (GDPR, HIPAA, SOC 2, PCI). Partner with data governance on quality, stewardship, and master data management. Provide architectural guidance, design reviews, and mentorship to data engineers, ML engineers, and analysts. Influence executive stakeholders; translate business needs into roadmaps and ROI-backed proposals. Evaluate emerging technologies and produce reference architectures, POCs, and best practices. Required Qualifications 12 years in data engineering, data architecture, or analytics, with 5 years in architect-level roles. 3 years of hands-on Snowflake architecture at enterprise scale (SnowPro Advanced: Architect preferred). Deep expertise in data modeling (3NF, dimensional, Data Vault) and semantic layer design. Proven delivery of GenAI/agentic AI solutions in production (RAG, tool-calling agents, multi-agent workflows). Strong SQL and Python; experience with dbt, Airflow/Dagster, Kafka, and CI/CD (Git, Terraform). Experience on at least one major cloud (AWS, Azure, or GCP). Solid understanding of data governance, security, and privacy frameworks. Excellent communication, stakeholder management, and leadership skills. Preferred Qualifications SnowPro Advanced certifications (Architect, Data Engineer, Data Scientist) and cloud architect certifications. Experience with knowledge graphs/ontologies (RDF/OWL, Neo4j) and graph-RAG. Experience with vector databases and embedding strategies. Background in MLOps and feature stores. Industry experience in BFSI / Healthcare / Retail / Manufacturing . Contributions to architecture blogs, talks, or open-source.
10/28/2026
Full time
Job Description Job Description Interviews: two internal rounds, one customer Experience: Minimum 12 years Job Description: About the Role We are looking for a Principal AI & Data Architect to define and lead our enterprise data and AI architecture. You will design a Snowflake-centric data platform with a strong semantic layer, and build the foundations for agentic AI systems that reason over trusted, governed enterprise data. You will be a hands-on technical leader, partnering with business, engineering, and security teams to turn data into reliable, AI-ready products. Key Responsibilities Data Architecture & Snowflake Platform Own the end-to-end architecture of the Snowflake Data Cloud: ingestion, storage, transformation, serving, and consumption. Design scalable, cost-efficient solutions using Snowflake features such as Snowpipe, Streams & Tasks, Dynamic Tables, Snowpark, Iceberg tables, Secure Data Sharing, and Marketplace. Define standards for performance tuning, warehouse sizing, clustering, and FinOps/cost governance. Lead modernization and migration from legacy platforms (Teradata, Oracle, Hadoop, SQL Server) to Snowflake. Semantic & Data Modeling Architect enterprise semantic layers, including business metrics, dimensions, hierarchies, and entity relationships. Design dimensional (Kimball), Data Vault 2.0, and canonical/domain models, and map them to the semantic layer. Implement Snowflake Semantic Views and Cortex Analyst semantic models, and integrate with tools like dbt Semantic Layer/MetricFlow, AtScale, Cube, or LookML. Establish ontologies, knowledge graphs, and business glossaries to ensure consistent meaning across the enterprise. Own metadata, lineage, and data contracts across domains (data mesh / data product approach). Agentic AI & GenAI Architecture Design agentic AI architectures: multi-agent orchestration, tool use, planning, memory, and guardrails. Build solutions on Snowflake Cortex (Cortex Agents, Cortex Analyst, Cortex Search, AI functions) and integrate with LLMs and frameworks such as LangGraph, LangChain, LlamaIndex, AutoGen, or CrewAI. Implement RAG and text-to-SQL patterns grounded in the semantic layer for accurate, explainable answers. Leverage MCP (Model Context Protocol) and API/tool integrations to expose governed data and actions to agents. Define LLMOps/AgentOps practices: evaluation, observability, prompt/version management, human-in-the-loop, and cost control. Establish Responsible AI practices covering bias, hallucination, privacy, and auditability. Governance, Security & Leadership Implement RBAC, row/column-level security, dynamic masking, tagging, and compliance controls (GDPR, HIPAA, SOC 2, PCI). Partner with data governance on quality, stewardship, and master data management. Provide architectural guidance, design reviews, and mentorship to data engineers, ML engineers, and analysts. Influence executive stakeholders; translate business needs into roadmaps and ROI-backed proposals. Evaluate emerging technologies and produce reference architectures, POCs, and best practices. Required Qualifications 12 years in data engineering, data architecture, or analytics, with 5 years in architect-level roles. 3 years of hands-on Snowflake architecture at enterprise scale (SnowPro Advanced: Architect preferred). Deep expertise in data modeling (3NF, dimensional, Data Vault) and semantic layer design. Proven delivery of GenAI/agentic AI solutions in production (RAG, tool-calling agents, multi-agent workflows). Strong SQL and Python; experience with dbt, Airflow/Dagster, Kafka, and CI/CD (Git, Terraform). Experience on at least one major cloud (AWS, Azure, or GCP). Solid understanding of data governance, security, and privacy frameworks. Excellent communication, stakeholder management, and leadership skills. Preferred Qualifications SnowPro Advanced certifications (Architect, Data Engineer, Data Scientist) and cloud architect certifications. Experience with knowledge graphs/ontologies (RDF/OWL, Neo4j) and graph-RAG. Experience with vector databases and embedding strategies. Background in MLOps and feature stores. Industry experience in BFSI / Healthcare / Retail / Manufacturing . Contributions to architecture blogs, talks, or open-source.
Job Description Job Description OVERVIEW Releady is partnering with a leading healthcare technology company to hire a Data Engineer, Principal for its Data Services team. This organization provides the technology backbone and shared data infrastructure for nonprofit, community, and regional health plans nationwide, unifying clinical, claims, demographic, and provider data into a single governed platform that powers automation and AI deployment across core health plan operations. This role reports to a Senior Manager, Data Solutions, or Director, and partners with Enterprise Architects, Portfolio, Analytics, and Data Engineering teams to design technical solutions and build data products that meet enterprise-wide data needs. The Principal drives data product delivery by designing and implementing cloud data lakes, data warehouse, and data mart solutions, and is expected to influence enterprise architecture decisions and mentor senior engineering talent. NOTE: Must be eligible to work on W2 without sponsorship. Not eligible for C2C. Pay Rate: $85-$95/hr Duration: 6-month contract-to-hire Location: Hybrid or Remote, however must reside in the following states: WA, OH, CA, AZ, CO, CT, FL, GA, MD, MN, NV, OR, AL, IL, VA, WI, TX, NY RESPONSIBILITIES Data Platform Architecture & Delivery Lead the design, development, and implementation of scalable data pipelines supporting enterprise data lakes, data warehouses, and data marts. Engineer robust ELT/ETL solutions that ingest, process, and curate structured and semi-structured data from diverse internal and external sources. Apply advanced data modeling techniques, including Data Vault 2.0, dimensional, and domain-oriented models, to support analytics and data products. Cross-Functional Solution Design Partner with Solution Design, Architecture, and Product teams to ensure technical designs are implemented accurately, efficiently, and securely. Build and optimize data solutions on cloud platforms such as Snowflake, Databricks, and Synapse, with a focus on performance, scalability, reliability, and cost efficiency. Quality, Governance & Operations Implement data quality, validation, observability, lineage, and governance controls embedded directly into data pipelines. Champion and apply DevOps and DataOps best practices, including CI/CD, automated testing, infrastructure as code, monitoring, and alerting. Identify performance bottlenecks, reliability risks, and optimization opportunities across data platforms and workflows. Technical Leadership & AI Enablement Provide hands-on technical leadership and mentorship to senior and mid-level data engineers, promoting engineering standards and best practices. Collaborate using agile methodologies to plan work, refine technical stories, and deliver iteratively with predictable outcomes. Support integration of AI/ML-ready data assets, ensuring data is trustworthy, well-modeled, and accessible for advanced analytics use cases. Act as a technical thought leader, advocating for modern data engineering patterns, tools, and practices aligned to enterprise strategy. QUALIFICATIONS Bachelor's degree or equivalent experience, with a minimum of ten years of relevant data engineering experience. Experience supporting enterprise AI/ML, advanced analytics, and data product ecosystems. Expertise in Data Vault 2.0, dimensional modeling, Lakehouse architecture, or domain-driven data design. Demonstrated ability to influence enterprise architecture decisions and mentor senior engineering talent. Expert-level understanding of data management practices, including data modeling (Data Vault 2.0), master data management, data integration, architecture, virtualization, warehousing, privacy, and security. Demonstrated enthusiasm for AI and emerging technologies, with hands-on experience applying AI-driven solutions in enterprise environments. Hands-on experience with SQL, Python, DBT Cloud, and DBT Core; expert-level fluency in NoSQL and database platforms such as Snowflake, Synapse, or Databricks. Proven ability to design and scale large-volume, high-performance data platforms leveraging parallel and distributed architectures. Advanced knowledge of CI/CD, source control, and agile delivery tooling such as Git, Bitbucket, and Jira. Experience with Airflow or Tidal (migrating from Tidal; comparable orchestration tools considered) Experience in healthcare, regulated environments, or large enterprises is strongly preferred. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or other non-merit factor. We are committed to creating a diverse and inclusive environment for all employees.
10/28/2026
Full time
Job Description Job Description OVERVIEW Releady is partnering with a leading healthcare technology company to hire a Data Engineer, Principal for its Data Services team. This organization provides the technology backbone and shared data infrastructure for nonprofit, community, and regional health plans nationwide, unifying clinical, claims, demographic, and provider data into a single governed platform that powers automation and AI deployment across core health plan operations. This role reports to a Senior Manager, Data Solutions, or Director, and partners with Enterprise Architects, Portfolio, Analytics, and Data Engineering teams to design technical solutions and build data products that meet enterprise-wide data needs. The Principal drives data product delivery by designing and implementing cloud data lakes, data warehouse, and data mart solutions, and is expected to influence enterprise architecture decisions and mentor senior engineering talent. NOTE: Must be eligible to work on W2 without sponsorship. Not eligible for C2C. Pay Rate: $85-$95/hr Duration: 6-month contract-to-hire Location: Hybrid or Remote, however must reside in the following states: WA, OH, CA, AZ, CO, CT, FL, GA, MD, MN, NV, OR, AL, IL, VA, WI, TX, NY RESPONSIBILITIES Data Platform Architecture & Delivery Lead the design, development, and implementation of scalable data pipelines supporting enterprise data lakes, data warehouses, and data marts. Engineer robust ELT/ETL solutions that ingest, process, and curate structured and semi-structured data from diverse internal and external sources. Apply advanced data modeling techniques, including Data Vault 2.0, dimensional, and domain-oriented models, to support analytics and data products. Cross-Functional Solution Design Partner with Solution Design, Architecture, and Product teams to ensure technical designs are implemented accurately, efficiently, and securely. Build and optimize data solutions on cloud platforms such as Snowflake, Databricks, and Synapse, with a focus on performance, scalability, reliability, and cost efficiency. Quality, Governance & Operations Implement data quality, validation, observability, lineage, and governance controls embedded directly into data pipelines. Champion and apply DevOps and DataOps best practices, including CI/CD, automated testing, infrastructure as code, monitoring, and alerting. Identify performance bottlenecks, reliability risks, and optimization opportunities across data platforms and workflows. Technical Leadership & AI Enablement Provide hands-on technical leadership and mentorship to senior and mid-level data engineers, promoting engineering standards and best practices. Collaborate using agile methodologies to plan work, refine technical stories, and deliver iteratively with predictable outcomes. Support integration of AI/ML-ready data assets, ensuring data is trustworthy, well-modeled, and accessible for advanced analytics use cases. Act as a technical thought leader, advocating for modern data engineering patterns, tools, and practices aligned to enterprise strategy. QUALIFICATIONS Bachelor's degree or equivalent experience, with a minimum of ten years of relevant data engineering experience. Experience supporting enterprise AI/ML, advanced analytics, and data product ecosystems. Expertise in Data Vault 2.0, dimensional modeling, Lakehouse architecture, or domain-driven data design. Demonstrated ability to influence enterprise architecture decisions and mentor senior engineering talent. Expert-level understanding of data management practices, including data modeling (Data Vault 2.0), master data management, data integration, architecture, virtualization, warehousing, privacy, and security. Demonstrated enthusiasm for AI and emerging technologies, with hands-on experience applying AI-driven solutions in enterprise environments. Hands-on experience with SQL, Python, DBT Cloud, and DBT Core; expert-level fluency in NoSQL and database platforms such as Snowflake, Synapse, or Databricks. Proven ability to design and scale large-volume, high-performance data platforms leveraging parallel and distributed architectures. Advanced knowledge of CI/CD, source control, and agile delivery tooling such as Git, Bitbucket, and Jira. Experience with Airflow or Tidal (migrating from Tidal; comparable orchestration tools considered) Experience in healthcare, regulated environments, or large enterprises is strongly preferred. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or other non-merit factor. We are committed to creating a diverse and inclusive environment for all employees.
Job Description Job Description Principal Data Architect Seeking a Principal Data Architect to lead data architecture across Microsoft Dynamics 365, enterprise applications, and Azure data platforms. This role will focus on data modeling, integration, governance, and analytics enablement across ERP, CRM, MES, and PLM systems. Responsibilities Define enterprise data architecture across D365, ERP, CRM, MES, and PLM Design data models and integration patterns using APIs, Dataverse, ETL/ELT, and event-driven architecture Align operational systems with Azure data warehouse/lakehouse platforms Support data quality, governance, MDM, lineage, analytics, and AI initiatives Reduce data silos and point-to-point integrations Partner with engineering, application, and business teams Requirements 10 years in data architecture, data engineering, or enterprise architecture Strong Microsoft Dynamics 365 ERP/CRM experience Experience with D365 integrations and data models Strong Azure experience: Data Factory, Synapse, Fabric, Data Lake Experience with Dataverse, APIs, middleware, and data modeling Strong understanding of data governance and data quality Preferred MES / PLM integration experience Dual-write, BYOD, CDM Azure Event Grid / Service Bus Power BI / Fabric Manufacturing or supply-chain experience
10/28/2026
Full time
Job Description Job Description Principal Data Architect Seeking a Principal Data Architect to lead data architecture across Microsoft Dynamics 365, enterprise applications, and Azure data platforms. This role will focus on data modeling, integration, governance, and analytics enablement across ERP, CRM, MES, and PLM systems. Responsibilities Define enterprise data architecture across D365, ERP, CRM, MES, and PLM Design data models and integration patterns using APIs, Dataverse, ETL/ELT, and event-driven architecture Align operational systems with Azure data warehouse/lakehouse platforms Support data quality, governance, MDM, lineage, analytics, and AI initiatives Reduce data silos and point-to-point integrations Partner with engineering, application, and business teams Requirements 10 years in data architecture, data engineering, or enterprise architecture Strong Microsoft Dynamics 365 ERP/CRM experience Experience with D365 integrations and data models Strong Azure experience: Data Factory, Synapse, Fabric, Data Lake Experience with Dataverse, APIs, middleware, and data modeling Strong understanding of data governance and data quality Preferred MES / PLM integration experience Dual-write, BYOD, CDM Azure Event Grid / Service Bus Power BI / Fabric Manufacturing or supply-chain experience
Job Description Job Description Network Engineer/ Network Architect position with our client. This is a high level role Need to architect, design and build.And standup a network platform in the cloud. Location- Remote There is a ROPES assessment that needs to be done They are looking for a principal level Network Engineer that can architect, design and build. They are looking for someone that has extensive experience with Cisco Viptela SD-Wan, Cloud security Architecture, and Palo Alto Firewalls. This role will be responsible for designing, implementing, and operating enterprise firewall and SD-WAN solutions across both cloud and on-premises environments. The ideal candidate will lead the deployment of Palo Alto firewalls within Google Cloud Platform (GCP) and other cloud environments, while also helping establish a new Cisco SD-WAN architecture connecting GCP hubs to on-premises branch and data center spokes. This position requires a highly independent engineer capable of driving both strategic initiatives and day-to-day operational support. GCP experience is not required, but preferred. They just need that expertise in leading the deployment within any cloud.
10/28/2026
Full time
Job Description Job Description Network Engineer/ Network Architect position with our client. This is a high level role Need to architect, design and build.And standup a network platform in the cloud. Location- Remote There is a ROPES assessment that needs to be done They are looking for a principal level Network Engineer that can architect, design and build. They are looking for someone that has extensive experience with Cisco Viptela SD-Wan, Cloud security Architecture, and Palo Alto Firewalls. This role will be responsible for designing, implementing, and operating enterprise firewall and SD-WAN solutions across both cloud and on-premises environments. The ideal candidate will lead the deployment of Palo Alto firewalls within Google Cloud Platform (GCP) and other cloud environments, while also helping establish a new Cisco SD-WAN architecture connecting GCP hubs to on-premises branch and data center spokes. This position requires a highly independent engineer capable of driving both strategic initiatives and day-to-day operational support. GCP experience is not required, but preferred. They just need that expertise in leading the deployment within any cloud.
Job Description Job Description Software Guidance & Assistance, Inc., (SGA), is searching for a Principal Data Scientist for a direct hire opportunity with one of our premier clients in Oshkosh, WI or New Hudson, MI. The Data Science Lead serves as a hands-on technical leader who bridges business strategy, advanced analytics, and AI-driven innovation to deliver high-impact solutions across the organization. This individual contributor role requires 5 years of experience leading end-to-end data science initiatives, partnering directly with business stakeholders, and translating complex business challenges into scalable machine learning, predictive analytics, and Generative AI solutions. The ideal candidate combines strong technical expertise in Python, SQL, cloud platforms, and modern AI/LLM technologies with the ability to independently architect, deploy, and support production-ready solutions. Data Science Lead collaborates closely with executive leadership, operations, product teams, and IT partners to define AI roadmaps, drive adoption, establish technical standards, and deliver measurable business value through data-driven decision making. Core requirements 5 years of experience; 6 years may be appropriate , according to the manager. The same core profile as R50808: AI-savvy and business-savvy, with strong business relationships and experience working directly with business stakeholders not solely back-end development. Ability to manage work end to end and personally deploy and deliver the solution. Shared considerations Both roles are individual-contributor positions , not manager roles. The manager is open to candidates who began in a business function or as a business analyst and later moved into IT, analytics, or data science, as well as candidates from consulting. The roles are described as hybrid: 3 days onsite and 2 remote , based in Oshkosh, Wisconsin, or New Hudson, Michigan . Relocation is acceptable if the candidate is willing to relocate; the manager said these are not commuting positions. Mentoring and executive-level communication are more central to the Principal role than to the Lead role. SUMMARY The Data Science Lead serves at the vital intersection of enterprise business strategy, machine learning innovation, and technical delivery. In this role, you will lead the strategic vision, architectural design, and operational deployment of predictive modeling, advanced analytics, and artificial intelligence solutions across key business units. Technical Leadership & Solution Architecture End-to-End Delivery: Architect, build, and deploy production-grade machine learning models, statistical frameworks, and Generative AI/LLM applications (e.g., RAG architectures, intelligent agents, and fine-tuned models). Engineering Standards: Establish best-in-class coding, testing, evaluation, and documentation standards across the team. Conduct regular code and architecture reviews. Production MLOps: Partner closely with Data Engineering and DevOps teams to establish robust CI/CD pipelines, automated model monitoring, feature stores, data drift detection, and automated retraining workflows. Research & Innovation: Stay abreast of state-of-the-art developments in AI/ML, evaluating emerging methodologies, tools, and frameworks to accelerate organizational capabilities. Strategy, Road mapping & Stakeholder Management Business Translation: Collaborate closely with executive leadership, product managers, operations, and commercial leaders to translate complex business challenges into actionable data science initiatives. Strategic Roadmap: Define and prioritize the enterprise AI and analytics roadmap, aligning project timelines, milestones, and deliverables with core business objectives. Value Realization & Communication: Articulate complex algorithmic methodologies and quantitative findings in clear, non-technical language to executive stakeholders, driving adoption and demonstrable business impact. Governance & Ethical AI: Champion data integrity, security, model explainability, algorithmic fairness, and compliance with organizational policies and international AI safety standards. People Leadership & Team Development Mentorship & Coaching: Lead, coach, and support junior and mid-level data scientists, nurturing individual career trajectories, continuous learning, and technical mastery. Agile Project Execution: Foster an agile, delivery-focused sprint cadence, balancing exploratory research with strict milestone deadlines and business commitments. Culture & Community: Cultivate an inclusive, collaborative culture that celebrates technical curiosity, innovation, and knowledge-sharing across cross-functional units. Education & Professional Experience Master's degree or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, Operations Research, or a related quantitative discipline (or equivalent practical experience). Minimum of 6 years of professional experience in data science, predictive modeling, or machine learning engineering. Technical Expertise Expert proficiency in Python (including NumPy, Pandas, Scikit-Learn, PyTorch, or TensorFlow) and advanced SQL. Strong hands-on experience building supervised/unsupervised learning pipelines, deep learning models, natural language processing (NLP), and modern Large Language Model (LLM) architectures. Proven track record utilizing enterprise cloud ecosystems (AWS, Azure, or GCP) and distributed compute systems (Databricks, Snowflake, Apache Spark). Demonstrated familiarity with model tracking, containerization, and orchestration platforms (e.g., MLflow, Docker, Kubernetes, Kubeflow, Airflow). Proficiency in presenting findings via business intelligence and visualization tools (e.g., Power BI, Streamlit). Soft Skills & Core Competencies Strategic Thinking: Ability to see the bigger picture, connecting data capabilities to long-term business strategy. Outstanding verbal and written communication skills with the capability to influence senior leadership. Pragmatism & Value Orientation: Focus on business utility, avoiding over-engineering in favor of reliable, interpretable, and maintainable solutions. By applying for a job with SGA, you agree to allow SGA to process your application for this and future opportunities in accordance with our Privacy Policy. Also, to ensure timely processing, you agree to be contacted by our AI recruiter via email, text, or phone. Message frequency varies and data rates may apply, but you can reply STOP to any SMS message to opt-out of texts and may contact SGA at to opt-out of AI communications. The choice not to engage with AI will not adversely impact your consideration for placement. AI is not used to make any hiring determinations. SGA is a technology and resource solutions provider driven to stand out. We are a women-owned business. Our mission: to solve big IT problems with a more personal, boutique approach. Each year, we match consultants like you to more than 1,000 engagements. When we say let's work better together, we mean it. You'll join a diverse team built on these core values: customer service, employee development, and quality and integrity in everything we do. Be yourself, love what you do and find your passion at work. Please find us at . SGA is an Equal Opportunity Employer and does not discriminate on the basis of Race, Color, Sex, Sexual Orientation, Gender Identity, Religion, National Origin, Disability, Veteran Status, Age, Marital Status, Pregnancy, Genetic Information, or Other Legally Protected Status. We are committed to providing access, equal opportunity, and reasonable accommodation for individuals with disabilities in employment, and our services, programs, and activities. Please visit our company EEO page to request an accommodation or assistance regarding our policy.
10/28/2026
Full time
Job Description Job Description Software Guidance & Assistance, Inc., (SGA), is searching for a Principal Data Scientist for a direct hire opportunity with one of our premier clients in Oshkosh, WI or New Hudson, MI. The Data Science Lead serves as a hands-on technical leader who bridges business strategy, advanced analytics, and AI-driven innovation to deliver high-impact solutions across the organization. This individual contributor role requires 5 years of experience leading end-to-end data science initiatives, partnering directly with business stakeholders, and translating complex business challenges into scalable machine learning, predictive analytics, and Generative AI solutions. The ideal candidate combines strong technical expertise in Python, SQL, cloud platforms, and modern AI/LLM technologies with the ability to independently architect, deploy, and support production-ready solutions. Data Science Lead collaborates closely with executive leadership, operations, product teams, and IT partners to define AI roadmaps, drive adoption, establish technical standards, and deliver measurable business value through data-driven decision making. Core requirements 5 years of experience; 6 years may be appropriate , according to the manager. The same core profile as R50808: AI-savvy and business-savvy, with strong business relationships and experience working directly with business stakeholders not solely back-end development. Ability to manage work end to end and personally deploy and deliver the solution. Shared considerations Both roles are individual-contributor positions , not manager roles. The manager is open to candidates who began in a business function or as a business analyst and later moved into IT, analytics, or data science, as well as candidates from consulting. The roles are described as hybrid: 3 days onsite and 2 remote , based in Oshkosh, Wisconsin, or New Hudson, Michigan . Relocation is acceptable if the candidate is willing to relocate; the manager said these are not commuting positions. Mentoring and executive-level communication are more central to the Principal role than to the Lead role. SUMMARY The Data Science Lead serves at the vital intersection of enterprise business strategy, machine learning innovation, and technical delivery. In this role, you will lead the strategic vision, architectural design, and operational deployment of predictive modeling, advanced analytics, and artificial intelligence solutions across key business units. Technical Leadership & Solution Architecture End-to-End Delivery: Architect, build, and deploy production-grade machine learning models, statistical frameworks, and Generative AI/LLM applications (e.g., RAG architectures, intelligent agents, and fine-tuned models). Engineering Standards: Establish best-in-class coding, testing, evaluation, and documentation standards across the team. Conduct regular code and architecture reviews. Production MLOps: Partner closely with Data Engineering and DevOps teams to establish robust CI/CD pipelines, automated model monitoring, feature stores, data drift detection, and automated retraining workflows. Research & Innovation: Stay abreast of state-of-the-art developments in AI/ML, evaluating emerging methodologies, tools, and frameworks to accelerate organizational capabilities. Strategy, Road mapping & Stakeholder Management Business Translation: Collaborate closely with executive leadership, product managers, operations, and commercial leaders to translate complex business challenges into actionable data science initiatives. Strategic Roadmap: Define and prioritize the enterprise AI and analytics roadmap, aligning project timelines, milestones, and deliverables with core business objectives. Value Realization & Communication: Articulate complex algorithmic methodologies and quantitative findings in clear, non-technical language to executive stakeholders, driving adoption and demonstrable business impact. Governance & Ethical AI: Champion data integrity, security, model explainability, algorithmic fairness, and compliance with organizational policies and international AI safety standards. People Leadership & Team Development Mentorship & Coaching: Lead, coach, and support junior and mid-level data scientists, nurturing individual career trajectories, continuous learning, and technical mastery. Agile Project Execution: Foster an agile, delivery-focused sprint cadence, balancing exploratory research with strict milestone deadlines and business commitments. Culture & Community: Cultivate an inclusive, collaborative culture that celebrates technical curiosity, innovation, and knowledge-sharing across cross-functional units. Education & Professional Experience Master's degree or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, Operations Research, or a related quantitative discipline (or equivalent practical experience). Minimum of 6 years of professional experience in data science, predictive modeling, or machine learning engineering. Technical Expertise Expert proficiency in Python (including NumPy, Pandas, Scikit-Learn, PyTorch, or TensorFlow) and advanced SQL. Strong hands-on experience building supervised/unsupervised learning pipelines, deep learning models, natural language processing (NLP), and modern Large Language Model (LLM) architectures. Proven track record utilizing enterprise cloud ecosystems (AWS, Azure, or GCP) and distributed compute systems (Databricks, Snowflake, Apache Spark). Demonstrated familiarity with model tracking, containerization, and orchestration platforms (e.g., MLflow, Docker, Kubernetes, Kubeflow, Airflow). Proficiency in presenting findings via business intelligence and visualization tools (e.g., Power BI, Streamlit). Soft Skills & Core Competencies Strategic Thinking: Ability to see the bigger picture, connecting data capabilities to long-term business strategy. Outstanding verbal and written communication skills with the capability to influence senior leadership. Pragmatism & Value Orientation: Focus on business utility, avoiding over-engineering in favor of reliable, interpretable, and maintainable solutions. By applying for a job with SGA, you agree to allow SGA to process your application for this and future opportunities in accordance with our Privacy Policy. Also, to ensure timely processing, you agree to be contacted by our AI recruiter via email, text, or phone. Message frequency varies and data rates may apply, but you can reply STOP to any SMS message to opt-out of texts and may contact SGA at to opt-out of AI communications. The choice not to engage with AI will not adversely impact your consideration for placement. AI is not used to make any hiring determinations. SGA is a technology and resource solutions provider driven to stand out. We are a women-owned business. Our mission: to solve big IT problems with a more personal, boutique approach. Each year, we match consultants like you to more than 1,000 engagements. When we say let's work better together, we mean it. You'll join a diverse team built on these core values: customer service, employee development, and quality and integrity in everything we do. Be yourself, love what you do and find your passion at work. Please find us at . SGA is an Equal Opportunity Employer and does not discriminate on the basis of Race, Color, Sex, Sexual Orientation, Gender Identity, Religion, National Origin, Disability, Veteran Status, Age, Marital Status, Pregnancy, Genetic Information, or Other Legally Protected Status. We are committed to providing access, equal opportunity, and reasonable accommodation for individuals with disabilities in employment, and our services, programs, and activities. Please visit our company EEO page to request an accommodation or assistance regarding our policy.
Job Description Job Description Remote Pay Rate Range: $70.00 - $75.00/hr on W2 Livescan is required Position Description: A Principal Data Engineer is responsible for designing, implementing, and managing the data infrastructure of an organization. The position provides specialized technical expertise in data integration, data quality, data operations, data platform architecture, and data governance to ensure a reliable, scalable, and well-managed analytical environment. Skills: Excellent verbal and written communication skills; customer service orientation; strong analytical & business acumen; Excellent time management and organization abilities; with a proven capacity to handle multiple tasks simultaneously. Highly collaborative, yet capable of working independently with focus and self-direction on projects; Meticulous and dedicated to delivering high-quality work; and effective mentor, providing guidance and support to junior data engineers and database administrators Experience Required: Additional Experience Required Five (5) years of professional work experience specializing in Databricks with significant expertise in data engineering, data integration, data warehousing, and cloud computing. Five (5) years of experience in developing data pipelines using Python Three (3) years of experience in designing and developing Databricks medallion Lakehouse architecture, applying data governance, and data quality best practices One (1) year of experience in developing data models One (1) year of experience in Managing Azure Resources One (1) year of experience in automating Azure Data Resources using DataOps Education Required This classification requires the possession of a bachelor's in computer science, Data Engineering, or related field. Additional qualifying experience may be substituted for the required education on a year-for-year basis. Additional Information: California Resident Candidates Only. Work is expected to be mostly REMOTE, and interviews will be conducted via Microsoft TEAMS. Work schedule will be 4/40, 10-hour day within the M-TH work schedule at the discretion of the program manager. Work shift ranges from 7:15am to 6:00pm.
10/28/2026
Full time
Job Description Job Description Remote Pay Rate Range: $70.00 - $75.00/hr on W2 Livescan is required Position Description: A Principal Data Engineer is responsible for designing, implementing, and managing the data infrastructure of an organization. The position provides specialized technical expertise in data integration, data quality, data operations, data platform architecture, and data governance to ensure a reliable, scalable, and well-managed analytical environment. Skills: Excellent verbal and written communication skills; customer service orientation; strong analytical & business acumen; Excellent time management and organization abilities; with a proven capacity to handle multiple tasks simultaneously. Highly collaborative, yet capable of working independently with focus and self-direction on projects; Meticulous and dedicated to delivering high-quality work; and effective mentor, providing guidance and support to junior data engineers and database administrators Experience Required: Additional Experience Required Five (5) years of professional work experience specializing in Databricks with significant expertise in data engineering, data integration, data warehousing, and cloud computing. Five (5) years of experience in developing data pipelines using Python Three (3) years of experience in designing and developing Databricks medallion Lakehouse architecture, applying data governance, and data quality best practices One (1) year of experience in developing data models One (1) year of experience in Managing Azure Resources One (1) year of experience in automating Azure Data Resources using DataOps Education Required This classification requires the possession of a bachelor's in computer science, Data Engineering, or related field. Additional qualifying experience may be substituted for the required education on a year-for-year basis. Additional Information: California Resident Candidates Only. Work is expected to be mostly REMOTE, and interviews will be conducted via Microsoft TEAMS. Work schedule will be 4/40, 10-hour day within the M-TH work schedule at the discretion of the program manager. Work shift ranges from 7:15am to 6:00pm.
Job Description Job Description Duration: 12 Months Schedule: 07:15 AM - 06:00 PM ( 4-day work week, 10-hour day) Job Description: Position Description: A Principal Data Engineer is responsible for designing, implementing, and managing the data infrastructure of an organization. The position provides specialized technical expertise in data integration, data quality, data operations, data platform architecture, and data governance to ensure a reliable, scalable, and well-managed analytical environment. Skills Required: Excellent verbal and written communication skills; customer service orientation Strong analytical & business acumen; Excellent time management and organization abilities; with a proven capacity to handle multiple tasks simultaneously Highly collaborative, yet capable of working independently with focus and self-direction on projects; Meticulous and dedicated to delivering high-quality work Effective mentor, providing guidance and support to junior data engineers and database administrators. Additional Experience Required : Five (5) + years of professional work experience specializing in Databricks with significant expertise in data engineering, data integration, data warehousing, and cloud computing. Five (5) years of experience in developing data pipelines using Python. Three (3) + years of experience in designing and developing Databricks medallion Lakehouse architecture, applying data governance, and data quality best practices. One (1) year of experience in developing data models. One (1) year of experience in Managing Azure Resources. One (1) year of experience in automating Azure Data Resources using DataOps. Education Required : This classification requires the possession of a Bachelor's in Computer Science, Data Engineering, or related field. Additional qualifying experience may be substituted for the required education on a year-for-year basis. Additional Information : California Resident Candidates Only. Work is expected to be mostly REMOTE, and interviews will be conducted via Microsoft TEAMS. Work schedule will be 4/40, 10-hour day within the M-TH work schedule at the discretion of the program manager. Work shift ranges from 7:15am to 6:00pm. About US Tech Solutions: US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions. To know more about US Tech Solutions, please visit . US Tech Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. AI Statement: By applying, you acknowledge that AI-assisted tools may be used during hiring. IND01
10/28/2026
Full time
Job Description Job Description Duration: 12 Months Schedule: 07:15 AM - 06:00 PM ( 4-day work week, 10-hour day) Job Description: Position Description: A Principal Data Engineer is responsible for designing, implementing, and managing the data infrastructure of an organization. The position provides specialized technical expertise in data integration, data quality, data operations, data platform architecture, and data governance to ensure a reliable, scalable, and well-managed analytical environment. Skills Required: Excellent verbal and written communication skills; customer service orientation Strong analytical & business acumen; Excellent time management and organization abilities; with a proven capacity to handle multiple tasks simultaneously Highly collaborative, yet capable of working independently with focus and self-direction on projects; Meticulous and dedicated to delivering high-quality work Effective mentor, providing guidance and support to junior data engineers and database administrators. Additional Experience Required : Five (5) + years of professional work experience specializing in Databricks with significant expertise in data engineering, data integration, data warehousing, and cloud computing. Five (5) years of experience in developing data pipelines using Python. Three (3) + years of experience in designing and developing Databricks medallion Lakehouse architecture, applying data governance, and data quality best practices. One (1) year of experience in developing data models. One (1) year of experience in Managing Azure Resources. One (1) year of experience in automating Azure Data Resources using DataOps. Education Required : This classification requires the possession of a Bachelor's in Computer Science, Data Engineering, or related field. Additional qualifying experience may be substituted for the required education on a year-for-year basis. Additional Information : California Resident Candidates Only. Work is expected to be mostly REMOTE, and interviews will be conducted via Microsoft TEAMS. Work schedule will be 4/40, 10-hour day within the M-TH work schedule at the discretion of the program manager. Work shift ranges from 7:15am to 6:00pm. About US Tech Solutions: US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions. To know more about US Tech Solutions, please visit . US Tech Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. AI Statement: By applying, you acknowledge that AI-assisted tools may be used during hiring. IND01