269 jobs found

Job Description Job Description SteerBridge is a modern technology company delivering innovative, mission focused solutions to the U.S. Government and private sector. Leveraging deep expertise in federal acquisition, digital transformation, and emerging technologies, we deliver agile, commercial grade capabilities that accelerate operational effectiveness and drive measurable mission success. At the core of SteerBridge is our people-especially the veterans whose leadership, problem solving mindset, and commitment to excellence elevate every project we support. We don't simply hire exceptional talent; we cultivate it , creating meaningful career pathways for veterans, military spouses, and professionals who share our passion for advancing technology and strengthening the missions we serve. Position Overview SteerBridge is seeking a Data Architect (Mid-Level) to support operations and sustainment efforts for the Modern Disability Claims program. This role will focus on designing, building, and maintaining scalable data architectures that support claims intake, adjudication workflows, clinical and claims data integration, and performance analytics for the program. The ideal candidate has hands-on experience designing modern data solutions, developing data pipelines, and supporting enterprise analytics environments within cloud-based ecosystems. Key Responsibilities Design and implement scalable data architectures and data models that support analytics, reporting, and operational needs. Develop, maintain, and optimize ETL/ELT pipelines integrating data from multiple structured and unstructured sources. Build and maintain cloud-based data platforms, data warehouses, and related infrastructure. Collaborate with data scientists, engineers, and stakeholders to develop data solutions supporting machine learning and advanced analytics initiatives. Implement and maintain data governance, security, data quality, and integrity standards across data environments. Monitor and optimize database and data platform performance, scalability, reliability, and availability. Support data modernization initiatives, including migration and transformation of legacy data environments to modern cloud-based architectures. Required Qualifications Eligibility requirements: U.S. citizenship is required for this position under applicable federal contract requirements. Candidate must also be able to obtain and maintain the security clearance required for the role, including a Public Trust clearance; an active Secret or Top Secret clearance also satisfies this requirement. Bachelor's degree in Computer Science, Systems Engineering, Data Science, or a related field. 3+ years of experience in data architecture, with demonstrated ownership of enterprise data warehouse design. Strong proficiency with Python, SQL, Pandas, PySpark, NumPy, and Git. Experience with data warehousing technologies such as Databricks, Amazon Redshift, Google BigQuery, or Apache Hive. Experience developing and automating large-scale data environments. Preferred Qualifications Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. Experience designing conceptual, logical, and physical data models and modern data lake and data warehouse architectures across AWS, Azure, or GCP. Experience with big data and distributed computing technologies such as Apache Kafka, Airflow, Spark, or NiFi. Experience supporting AI/ML workflows, analytics platforms, and large-scale data processing environments. Knowledge of data governance, security, compliance, CI/CD pipelines, and software development best practices. Experience supporting defense, healthcare, benefits administration, or other mission-critical federal programs. Benefits Health insurance Dental insurance Vision insurance Life Insurance 401(k) Retirement Plan with matching Paid Time Off Paid Federal Holidays The posted compensation range reflects the scope and requirements of this position. A final offer will be determined based on the candidate's relevant experience, skills, education, certifications, and work location, along with the responsibilities of the position. Where applicable, contract requirements, wage determinations, and federal contract labor categories may also inform the offer. SteerBridge also offers benefits that may include health and life insurance, paid time off, paid holidays, disability coverage, retirement savings, and professional development opportunities. Benefits vary by position and eligibility. SteerBridge is proud to be an Equal Opportunity Employer. We are committed to creating a diverse and inclusive workplace where all qualified applicants and employees are treated with respect and dignity-regardless of race, color, gender, age, religion, national origin, ancestry, disability, veteran status, genetic information, sexual orientation, or any other characteristic protected by law. We also provide reasonable accommodations for individuals with disabilities in accordance with applicable laws. If you require assistance during the application process, we encourage you to reach out so we can support your needs. SteerBridge is proud to be an Equal Opportunity Employer. We are committed to creating a diverse and inclusive workplace where all qualified applicants and employees are treated with respect and dignity-regardless of race, color, gender, age, religion, national origin, ancestry, disability, veteran status, genetic information, sexual orientation, or any other characteristic protected by law. We also provide reasonable accommodations for individuals with disabilities in accordance with applicable laws. If you require assistance during the application process, we encourage you to reach out so we can support your needs. If you would like information about how your application is processed, please contact us.

Job Description Job Description Data, AI, and Automation Specialist The Position: Censeo Consulting Group is seeking Data, AI, & Automation Specialists at Mid and Senior experience levels to support the General Services Administration (GSA) Assisted Acquisition Services (AAS) organization through the Contracted Enterprise Support (ACES) program. Data, AI, & Automation Specialists will help identify, design, develop, and implement data-driven and technology-enabled solutions that improve how teams analyze information, manage workflows, and execute business processes. In this role, you will collaborate with government stakeholders, business users, analysts, and technical teams to identify opportunities for automation and artificial intelligence, improve access to actionable data, and translate operational needs into practical solutions. This position is ideal for experienced professionals who combine strong technical and analytical capabilities with an understanding of business processes and can effectively translate complex requirements into scalable data, AI, and automation solutions. Key Responsibilities: Analyze business processes, workflows, data sources, and operational requirements to identify opportunities for improvement through data, AI, and automation. Design, develop, implement, and support automated workflows, analytical solutions, dashboards, and other technology-enabled tools. Work with government stakeholders and business users to gather requirements and translate operational challenges into technical and analytical solutions. Develop data models, queries, reports, dashboards, and visualizations that provide stakeholders with actionable insights. Support the development and implementation of AI-enabled solutions that improve analysis, knowledge management, decision support, or business operations. Design and implement workflow and process automations that reduce manual effort, streamline repetitive activities, and improve operational consistency. Integrate information from multiple data sources to support reporting, analysis, and decision-making. Evaluate data quality, identify gaps or inconsistencies, and support improvements to data collection, organization, and management. Develop prototypes and proof-of-concept solutions to evaluate potential approaches to business and operational challenges. Test, troubleshoot, maintain, and improve data, AI, and automation solutions. Develop documentation, user guidance, technical materials, and presentations to support solution implementation and adoption. Collaborate with technical, acquisition, financial, program, and operational stakeholders to ensure solutions align with business requirements. Monitor solution performance and identify opportunities for enhancement, optimization, and expanded automation. Support responsible implementation of AI and automation within applicable federal security, privacy, data governance, and technology requirements. Provide technical guidance and recommendations to government stakeholders and project teams. The Ideal Candidate: At Censeo, we are looking for unique candidates whose passion and enthusiasm will help shape Censeo's client insights and workplace culture. Our staff have a wide range of backgrounds, areas of expertise, personality types, and favorite breakfast foods. Our client and cultural successes are rooted in our team's innovation, creative problem solving, and collaboration. The unique perspective that you bring and the way you tackle problems are much more important to us than what's printed on your diploma. We believe an effective Data, AI, and Automation Specialist will be able to combine strategic thinking, analytical judgment, and strong people skills to identify and implement meaningful, practical changes for federal clients. Qualifications for the role include: Bachelor's degree in computer science, information systems, data science, engineering, business analytics, mathematics, statistics, or a related discipline, or equivalent relevant professional experience. Experience developing or implementing data analytics, AI, automation, business intelligence, or technology-enabled business solutions. Experience translating business requirements and operational challenges into practical technical solutions. Strong analytical, critical-thinking, and problem-solving skills. Experience working with structured and unstructured data and integrating information from multiple sources. Experience developing dashboards, visualizations, reports, automated workflows, or analytical applications. Familiarity with AI, machine learning, generative AI, intelligent automation, or related technologies. Experience with relevant tools and technologies such as Power BI, Power Automate, Power Apps, Python, SQL, or comparable platforms and programming languages. Ability to evaluate processes and identify opportunities for automation and technology-enabled improvement. Strong written and verbal communication skills, including the ability to explain technical concepts to non-technical stakeholders. Experience documenting technical requirements, solution designs, processes, testing results, and user guidance. Ability to manage multiple technical initiatives and competing priorities. Experience supporting federal government technology, data, automation, acquisition, or business transformation initiatives is preferred. Experience supporting GSA or another federal government agency is preferred. Relevant Microsoft, data analytics, cloud, AI, automation, or project management certifications are a plus. Experience Levels: Mid Level: 5+ years of experience in data analytics, artificial intelligence, automation, business intelligence, software development, data engineering, process automation, technology consulting, or a closely related field. Senior Level: 10+ years of experience in data analytics, artificial intelligence, automation, business intelligence, software development, data engineering, process automation, technology consulting, or a closely related field. The Company: Censeo Consulting Group is a top Washington D.C. based management consulting firm dedicated to helping public sector and non-profit clients build operational excellence, deliver better outcomes, and lower cost. We take a personalized approach to strategic consulting to solve our clients' most complex problems and build operational excellence that transforms their organizations, allowing them to better deliver on their public and social missions. At Censeo, our award-winning culture means you'll join a tight-knit community of 75 brilliant and passionate colleagues. We are advocates for a better functioning public sector, and we're also good friends who know the names of each other's dogs. Our philosophy is horizontal, not hierarchical, and our open-door policy encourages a culture of entrepreneurship at all levels. We share successes, make decisions together, and foster an environment for those with passion and initiative to lead. Our colleagues bring their own unique personalities to work every day and use them to help shape our growing firm in ways that reach far beyond client projects. The Location: Censeo Consulting Group is based in Washington D.C., a fantastic city for working professionals. We work in a hybrid setting with flexibility to work from home and work in our office conveniently located in the heart of downtown, just a few blocks away from the White House. And with many of our clients also based in D.C., we have the luxury of leaving for a meeting and being back in the office in time for post-work happy hours, team dinners, and game nights. The Fine Print: The salary range for this role is $110,000 - $170,000 depending on experience This is an exempt, full-time position This role is subject to a full-time in-person work schedule in Washington, D.C. with the possibility for hybrid if approved by the client. Essential Physical Functions Sitting: Particularly for sustained periods of time Light Carrying: Physically transporting items weighing less than 15 pounds from one location to another Censeo offers a competitive compensation and benefits package, including paid vacation and sick leave, flexible and remote work opportunities, and tuition and training reimbursement. More information on our benefits and perks can be found at -us/. Censeo is an equal opportunity employer. We are committed to providing equal opportunity to all applicants and employees in full compliance with all applicable state and federal laws prohibiting discrimination on the basis of race, color, age, gender, religion, national origin, disability, protected veteran status, or any other class protected by applicable state or federal law. Join Our Award-Winning Culture! Our passion wins awards. But don't just take it from us 2024 Vault Consulting 50 North America 2024 Vault Best Consulting Firm for Hours in the Office 2023 Vault Best Consulting Firm for Work/Life Balance 2023 Vault Best Consulting Firm for Overall Diversity 2023 Management Consulted Best Boutique Firms in Washington DC 2022 Vault Best Overall Consulting Firm to Work For 2020 Vault Best Boutique Consulting Firm 2019 Ivy Exec Best Boutique Consulting Firm . click apply for full job details

About Innovative Labs We are a leading maker of liquid dietary supplements, known for our innovation, strong R&D, and focus on quality. With our in-house team, we create custom liquid products for top wellness, nutraceutical, and food brands. At Innovative Labs, we believe in teamwork and creativity. For over 15 years, we've helped brands bring new ideas to life with high-quality liquids, gels, purees, pastes, oils, and emulsions. Our modern facilities and dedicated team work together to make products that matter. Here, you'll grow, learn, and be part of a team that's always improving and moving forward. Why You'll Love Working Here • Your Work Matters: Support the Brands People Use Every Day • Collaborate & Create: Join a team that values fresh ideas, open communication, and teamwork • Grow Your Career: We encourage curiosity, learning, and stepping up to new challenges • Supportive Culture: Thrive in a workplace that values your contributions and well-being About the Job We are looking for a senior engineer to own the technology behind our manufacturing business. You will manage our enterprise infrastructure across cloud, on-premises and hosted environments, administer our ERP and the SaaS applications our teams rely on every day (lab, quality, production and project management), keep them all connected, and work with leaders across the company to put AI and automation to work for the business. You will be trusted to make decisions and see them through, with a direct effect on how the business runs. What You'll Do Infrastructure and Systems Administration Own our Microsoft Azure environment: Azure SQL, virtual machines, networking, storage, Azure Data Factory, identity and cost management Administer Microsoft 365 and Entra ID / Active Directory: accounts, groups, access control, conditional access and SSO Administer the VMware virtual environment and maintain the on-premises and cloud servers (Windows and Linux) behind our internal applications, including patching, backups, monitoring and disaster recovery Apply security best practices: least-privilege access, secrets management, MFA, logging, and regular access reviews AI and Automation Lead AI for the company: own our AI platform and tools, and drive how AI is adopted and used across every department Use AI as an everyday working tool: build, troubleshoot, document and support systems faster with AI assistants and agents (for example, Claude, Microsoft Copilot or Azure OpenAI) Bring systems engineering and AI together: use AI to improve how our systems and integrations work, and give the AI tools you put in place the same testing, security and monitoring as any other system Find and deliver ways to automate manual work across operations and the back office Stay current as AI changes: follow new models, tools and practices Keep learning, and help others learn: grow your own AI skills and help colleagues across the company use AI well Use AI responsibly: help set and follow practical rules for how the company uses AI, with the right controls around company data ERP and Business Systems Administration Act as the main technical administrator of our ERP: configuration, user security, upgrades, database health, and the reporting replica Administer our SaaS and specialized platforms, including LIMS, QMS, MES and production-performance (OEE) systems, and others as we add them Be the escalation point for system issues. Diagnose problems across systems, work with vendors to fix them, and keep vendor relationships and contracts in good order Evaluate new software, lead implementations and upgrades, and retire systems we no longer need Integrations and Development Design, build and support integrations between our satellite systems and the ERP, using REST APIs, Azure Data Factory, Databricks, SQL and scripting Own the data pipelines that keep production, inventory, quality and financial data in sync, with monitoring and alerts so failures are caught before users notice Write and maintain SQL, Python and PHP code for integrations, reports and internal web tools Keep clear documentation for integrations and development Partnership and Governance Partner with department leaders and teams to understand their business needs, then deliver the solution: configure an existing system, build an integration, or design a new tool on our internal web platform Support validation, change control and audit needs for systems that hold quality and compliance data Keep system documentation, runbooks and the system and integration inventory current What Makes You a Great Fit Bachelor's degree in Information Systems, Computer Science, Engineering or a related field, or equivalent professional experience 10+ years in IT systems engineering, enterprise systems administration or a similar role, with at least 5 of those years hands-on with cloud infrastructure Strong Microsoft Azure experience: Azure SQL, VMs, networking, identity (Entra ID), and Azure Data Factory or a comparable integration and data pipeline tool Experience administering an ERP system, ideally in a manufacturing or distribution business A track record of building and supporting system integrations using REST APIs, SQL and at least one scripting language (Python, PowerShell or similar) Strong SQL skills, including writing queries, tuning performance and troubleshooting databases (Microsoft SQL Server / Azure SQL preferred) Working knowledge of VMware, Active Directory, Microsoft 365, Windows Server and Linux administration Sound security habits: access control, secrets handling, backups and incident response Clear communication with non-technical users and leaders, and the ability to explain trade-offs in plain language The judgment to work independently and own outcomes, as a senior member of a small team Curiosity and adaptability: a habit of learning new technology quickly, and a real interest in using AI to change how work gets done Preferred Qualifications Experience in an FDA-regulated or cGMP manufacturing environment, including computer system validation and audit support Hands-on experience with LIMS, QMS, MES or OEE platforms (such as Redzone) Experience with Databricks, Snowflake or other modern data platforms Web development experience (PHP, JavaScript) for internal tools and dashboards Hands-on experience with AI coding assistants, AI agents or large language model APIs Experience with Git and CI/CD The Perks of Joining Our Team Comprehensive health, dental, and vision coverage-plus a few weeks of paid parental leave when it matters most Paid time off and holidays to help you unwind and recharge Real opportunities to grow your skills and make an impact as we evolve A collaborative team that's adaptable, supportive, and driven to succeed together A 401(k) retirement plan with company contributions to help you build your future Ready to innovate with us? Apply now and let's build the future together! PI60d229300da9-2914

Job Description We are seeking a Senior Anaplan Solutions Architect to set technical direction and lead connected planning for Corporate FP&A at a fast-growing technology company. In our lean team, you will be both architect and hands-on builder, independently guiding complex design decisions while coaching FP&A colleagues toward greater self-sufficiency. You will help advance a continuously updated, driver-based forecast grounded in business drivers, robust data, and validated machine-learning inputs, freeing Finance partners to advise the business and giving leaders timely projections. What you'll do: Architect and build connected models for financial statements, workforce, allocations, annual planning, and long-range scenarios. Shape the planning architecture and roadmap with Finance leaders, balancing business value, scalability, and delivery capacity. Establish design standards and resolve cross-model dependencies to keep planning solutions intuitive, performant, and maintainable. Coach FP&A users and builders to own more of their analysis, scenarios, and model development. Integrate trusted enterprise data and predictive outputs into Anaplan, partnering with data and analytics engineers. Advance continuously refreshed, driver-based forecasting with clear reconciliation, review, and override controls. Provide technical leadership to builders and implementation partners, owning solution quality, acceptance, and knowledge transfer. Required qualifications: Bachelor's degree with 8+ years of relevant experience, master's degree with 6+ years, or PhD with 3+ years, including hands-on Anaplan Extensive hands-on Anaplan experience with a record of architecting and delivering complex connected planning solutions Deep understanding of Corporate FP&A and the judgment to translate Finance priorities into architectural decisions Demonstrated ability to independently lead complex delivery while building directly in a lean team Experience with integrations, model performance, reconciliation, and controlled deployment Experience mentoring builders, developing Finance users, and advising senior stakeholders on design and delivery tradeoffs Preferred qualifications: Anaplan Solution Architect certification or Master Anaplanner designation Experience with integrated three-statement planning and driver-based forecasting Experience integrating predictive models or enterprise data platforms with planning applications Compensation: $130,000 - $200,000 per year Full-time regular employee offer package: pay within range listed + bonus + benefits + equity

Job Description Principal AI Solutions Architect About Us MathCo (TheMathCompany) is a global Enterprise AI and Analytics company trusted by Fortune 500 and Global 2000 enterprises for data-driven decision-making. Founded in 2016, MathCo builds custom AI and advanced analytics solutions focused on enterprise problem-solving through its innovative hybrid model. NucliOS, MathCo's proprietary platform with pre-built workflows and reusable plug-and-play modules, enables the vision of connected intelligence at a lower TCO. We foster an open, transparent, and collaborative culture with no barriers, making MathCo a great place to work. We offer exciting growth opportunities and value capabilities and attitude over experience-enabling our Mathemagicians to truly Leave a Mark. Role Overview We are seeking a Principal AI Solutions Architect with deep, hands-on experience building production GenAI and agentic systems. You will be the senior technical voice on our US AI engagements focused on AI-ready data and context foundations and on operating AI on an enterprise scale, across CPG, Retail, Life Sciences and other industries, turning that expertise into scalable applications that solve complex business problems. This is not a research role. We are looking for someone who has designed and implemented production AI solutions and knows what it takes to move from POCs to enterprise-scale applications. You will work on client opportunities from the first conversation through proposal, alongside our client and sales leaders, and with MathCo's global architecture and delivery teams, including our teams in India, so that every solution is technically sound and deliverable. The ideal candidate has worked deeply with LLMs, knowledge graphs, context engineering, agentic systems, AI orchestration, and modern AI and data platforms. What You'll Do Serve as a GenAI technical authority Provide senior technical credibility in strategic client and solutioning conversations with CTOs, CIOs, Chief Data Officers, AI leaders and business executives. Translate complex AI concepts into clear business implications, trade-offs and recommendations. Lead in-depth technical discussions on context layer, knowledge graphs, agents and AI operations in live client settings. Architect enterprise AI solutions Define end-to-end architectures that bring together LLMs, knowledge graphs, retrieval and context layers, agents, tools, orchestration frameworks and enterprise data. Develop architecture patterns that take AI applications from prototype to production. Evaluate options against business requirements, performance, scalability, security, maintainability and cost. Provide technical direction to engineering and delivery teams, and build a working prototype or demo when needed. Author and present the technical sections of proposals: architecture, phasing, assumptions and effort estimates. Build reusable reference architectures, scoping frameworks and platform-specific demos. Connect AI to business outcomes Work with clients to understand business processes and identify where AI can materially change how work gets done. Partner with business and consulting teams to shape AI opportunities into technically viable solutions. Build the business case: quantify the value and ROI of AI programs Design the data and context foundation Design how context is assembled and managed for AI systems across structured and unstructured enterprise knowledge. Design solutions using knowledge graphs, retrieval, memory, tools and other mechanisms that improve the relevance and reliability of LLM applications. Design the data foundation under AI applications: lakehouse and data-platform architecture, metadata and catalogs, semantic layers, data quality and access controls. Architect agentic systems, including tools, orchestration, guardrails and supporting infrastructure. Operationalize AI at enterprise scale Shape AI operations solutions: LLMOps, evaluation and monitoring, guardrails, and model and agent lifecycle management. Advise on AI cost: token usage and optimization, model selection and routing, and infrastructure trade-offs. Advise on AI governance and risk, including frameworks such as NIST AI RMF and the EU AI Act, data privacy (including HIPAA), security and audit. Develop points of view on emerging AI-at-scale topics with MathCo's innovation teams. What We're Looking For 10+ years in AI, machine learning, data or enterprise architecture, including 2+ years designing and shipping production GenAI / LLM applications. Hands-on experience building sophisticated AI applications with commercial and/or open-source foundation models. Strong knowledge of LLM application architecture, context engineering, knowledge graphs, retrieval and grounding, agentic AI and multi-step workflows, AI orchestration, and enterprise data integration. Working knowledge of lakehouse and data platforms (e.g., Databricks, Snowflake, BigQuery), semantic layers, metadata and catalogs. Working knowledge of evaluation, observability and LLMOps, AI cost optimization, and AI governance, privacy and security. Familiarity with leading model ecosystems (OpenAI, Anthropic, Google) and hyperscaler AI services Pre-sales, solutions engineering or consulting experience, including authoring and defending the technical sections of proposals and SOWs. Ability to explain why specific technical choices were made, to engineers and executives alike. Experience working with global delivery teams across time zones. Exposure to data and AI use cases in CPG, Retail or Life Sciences. What Will Differentiate You The strongest candidates will be able to demonstrate all three of the following: 1. Technical depth You understand the mechanics of modern AI systems deeply enough to engage with senior AI engineers, scientists and architects. 2. Architecture and implementation experience You can whiteboard an end-to-end AI architecture and explain how it would actually be implemented, including the decisions and trade-offs required to make it successful at enterprise scale. 3. Executive and client credibility You can take that same architecture into a client conversation and explain it in a way that builds confidence with both business and technical executives - including a value case a CFO would sign off on. What Success Looks Like You are the trusted technical voice on our AI data, context and scale engagements. Your proposal architectures are credible, clearly scoped and deliverable. The reference architectures, ROI models and demos you build are used across the team. You bring new points of view on operating AI at scale to our clients. Being a Mathemagician Embody MathCo's values of openness, ownership, and impact. Contribute actively to internal mentorship, innovation, and team development. Champion diversity, equity, and inclusion by valuing a variety of perspectives in problem-solving. Why Join Us? MathCo is recognized globally as a leader in enterprise AI and analytics: Leader in Generative AI Service Providers - PeMa Quadrant (AIMResearch) Named among North America's Inspiring Workplaces Accredited for Inclusive Practices - Great Place to Work Institute, India Recognized for DEIB Excellence - India's Best Workplaces for DEIB To learn more, visit

AI Engineer 4 (Gen AI Platform Services: Agentic Systems) 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. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $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 (Gen AI Platform Services: Agentic Systems) 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. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $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).

Job Description Job Description Role : Gen AI/Agentic AI Lead / AI Architect with GCP Location : Paramus, NJ 07652 (Onsite) Rate : 80 Hire Type (FTE/Contract): Contract Must have GCP and the Google AI stack (Vertex AI, Gemini). 1. Strong GCP ecosystem understanding - should know the data products and when to choose which product. 2. Past must be GCP Data Architect or Engineer 3. Present must be AI Architect - have strong hands-on experience on at least 1 AI project on GCP. We are seeking an experienced AI Architect to lead the design, development, and implementation of enterprise-scale Artificial Intelligence solutions. The ideal candidate will possess deep expertise in Generative AI, Large Language Models (LLMs), Agentic AI, and LLMOps, along with a proven track record of managing and directing AI engineering teams. This role requires strong technical leadership, strategic thinking, and the ability to drive AI innovation aligned with business objectives. Key Responsibilities 1. Define and drive the AI architecture strategy for enterprise-wide AI initiatives. 2. Design scalable and secure Generative AI, Agentic AI, and LLM-based solutions. 3. Lead the implementation of AI platforms, frameworks, and operational processes for LLMOps. 4. Establish best practices for model lifecycle management, monitoring, governance, and performance optimization. 5. Collaborate with business stakeholders to identify high-value AI use cases and develop solution roadmaps. 6. Provide technical leadership and mentorship to AI engineers, data scientists, and architects. 7. Oversee AI solution delivery, ensuring adherence to architecture standards, security, and compliance requirements. 8. Evaluate emerging AI technologies and recommend adoption strategies. 9. Drive innovation in autonomous AI systems, multi-agent frameworks, and enterprise AI transformation programs. Required Skills & Experience 12 years of overall IT experience with significant experience in Artificial Intelligence and Machine Learning. Strong expertise in: AI Architecture Generative AI (GenAI) Large Language Models (LLMs) LLMOps Agentic AI / Multi-Agent Systems AI Solution Design & Governance Experience building enterprise-grade AI applications using leading AI frameworks and platforms. Hands-on experience with AI orchestration frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar technologies. Strong understanding of AI deployment, monitoring, observability, security, and responsible AI practices. Proven experience leading, managing, and mentoring AI engineering and data science teams. Ability to engage with executive stakeholders and translate business requirements into AI solutions. Preferred Qualifications Experience in Traditional Data Science and Machine Learning. Experience with Google Cloud Platform AI ecosystem. Hands-on experience with BigQuery ML (BQML). Knowledge of MLOps, Data Engineering, and cloud-native AI architectures. Experience implementing AI solutions in large enterprise environments. Leadership Requirements Demonstrated success in directing and managing AI teams. Experience leading cross-functional initiatives involving Data Scientists, AI Engineers, Architects, and Business Stakeholders. Strong communication, stakeholder management, and decision-making skills. Education Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field. Relevant AI/Cloud certifications are highly preferred. Nice to Have Experience with Google Vertex AI, Gemini, OpenAI, Anthropic Claude, or similar AI ecosystems. Experience with RAG (Retrieval-Augmented Generation) architectures. Exposure to Data Engineering platforms such as BigQuery, Databricks, Snowflake, or equivalent technologies. Experience implementing Responsible AI and AI Governance frameworks. Ideal Candidate Profile

Job Description Job Description Data Architect / Data Engineering Lead Role Overview Seeking a senior Data Architect / Data Engineering Lead to establish enterprise data architectures and lead implementation of scalable data platforms supporting analytics, operational workloads, AI, and machine learning. Key Responsibilities Develop enterprise data architecture and target-state roadmaps. Design data lake, lakehouse, warehouse, operational and analytics platforms. Develop logical and physical data models. Architect batch and real-time data pipelines. Establish data integration and interoperability patterns. Lead ETL/ELT architecture and development. Establish data quality, lineage, metadata, governance, and master-data practices. Design data architectures supporting AI/ML and GenAI. Optimize data performance, scalability, availability, and cost. Work with security teams to protect sensitive data. Lead data engineers and provide technical direction. Support migration and modernization of legacy data environments. Mandatory Qualifications 10 years of data technology experience. 5 years in Data Architect or senior Data Engineering roles. Advanced SQL. ETL/ELT and data integration. Data warehouse/lake/lakehouse architectures. Cloud data platform experience. Data modeling and governance. Experience designing enterprise-scale pipelines. Highly Preferred Azure Data Factory. Azure Synapse. Microsoft Fabric. Databricks. Snowflake. Spark/PySpark. Kafka/event streaming. Purview. Power BI. AI/ML data architecture.

Job Description Job Description Immediate need for a talented Data Architect. This is a 12+months contract opportunity with long-term potential and is located in Columbus, IN (Onsite) . Please review the job description below and contact me ASAP if you are interested. Job ID:26-33600 Pay Range: $65 - $70/hour. Employee benefits include, but are not limited to, health insurance (medical, dental, vision), 401(k) plan, and paid sick leave (depending on work location). Key Responsibilities: Work Focus: 70%: Data Architecture, AI Governance, AI Agents, and Computer Vision 30%: DevOps, SecOps, and production deployment Data Architecture and Governance - 35% Define and implement enterprise data integration and storage strategies. Design scalable architectures for databases, data lakes, APIs, and analytics platforms. Develop physical, logical, and metadata models. Establish data quality, accuracy, ownership, lineage, retention, and access-control standards. Define governance metrics and monitor alignment with enterprise data strategies. Lead data migration, transformation, validation, and modernization activities. Align solution architecture with central enterprise architecture standards. Design and implement microservices and reusable data services. Monitor and optimize database performance, scalability, availability, and cost. Support analytics, reporting, and data-lake integration. AI Governance, AI Agents, and Knowledge Solutions - 25% Develop a strategy for making trusted enterprise data available to AI applications and agents. Define AI governance standards covering security, privacy, traceability, model risk, human oversight, and responsible AI. Identify and prioritize knowledge-based AI and agentic AI use cases. Design knowledge repositories, semantic search, vector databases, and retrieval-augmented generation solutions. Develop AI solutions from proof of concept through production readiness. Create reusable frameworks for subject-matter-expert agents and enterprise knowledge assistants. Establish long-term support, ownership, lifecycle, and sustainability plans for AI solutions. Define AI performance, accuracy, adoption, cost, and business-value metrics. Implement monitoring for model quality, data drift, hallucination risk, and solution reliability. Computer Vision - 10% Design and implement computer vision solutions for image and video analysis. Develop pipelines for image ingestion, annotation, preprocessing, model training, inference, and monitoring. Support use cases such as object detection, classification, OCR, defect identification, visual inspection, and document-image processing. Evaluate computer vision models and services based on accuracy, latency, scalability, explainability, and cost. Establish governance standards for image data, labeling quality, model validation, privacy, and retention. Deploy computer vision solutions using cloud, edge, or hybrid architectures. Transition computer vision prototypes into reliable production applications. DevOps and SecOps - 30% Establish software development, coding, documentation, testing, and code-review standards. Design and optimize CI/CD and DevSecOps pipelines. Automate application, infrastructure, database, and AI-model deployments. Integrate static code analysis, dependency scanning, container scanning, secret detection, and vulnerability management. Define encryption, identity, access-control, auditing, logging, and sensitive-data handling requirements. Ensure compliance with enterprise cybersecurity and regulatory requirements. Support containerized and microservices-based deployments. Implement monitoring, alerting, incident response, backup, recovery, and operational-support processes. Troubleshoot production issues and drive root-cause analysis and corrective actions. Develop implementation roadmaps in coordination with technical and business leadership. Key Requirements and Technology Experience: Bachelor's degree in Computer Science, Data Science, Software Engineering, Information Systems, Electrical Engineering, or a related technical field. Seven or more years of experience in data engineering, software development, cloud architecture, AI/ML, or related areas. Three or more years of experience designing enterprise data or solution architectures. Hands-on experience with AWS cloud services and cloud-native solution development. Strong experience with relational databases, NoSQL databases, data lakes, and data warehouses. Experience developing data integration pipelines using ETL/ELT, APIs, messaging, or event-driven architectures. Strong knowledge of data modeling, metadata management, data lineage, data quality, and governance. Experience developing or deploying AI, machine learning, generative AI, or knowledge-based solutions. Working knowledge of computer vision concepts and image-processing workflows. Experience implementing CI/CD pipelines and DevSecOps controls. Strong understanding of encryption, identity management, access controls, audit logging, and secure handling of sensitive data. Proficiency in Python and SQL. Experience with Git-based development, automated testing, and code-review practices. Ability to translate business requirements into scalable technical solutions. Strong communication skills with the ability to work across architecture, cybersecurity, engineering, IT, and business teams. Cloud: AWS, including services for compute, storage, databases, security, monitoring, and AI/ML Programming: Python, SQL, scripting, and API development Data Platforms: Relational databases, NoSQL, data lakes, data warehouses, and vector databases Data Integration: ETL/ELT, REST APIs, event streaming, messaging, and microservices AI: Generative AI, AI agents, RAG, prompt orchestration, embeddings, model evaluation, and responsible AI controls Computer Vision: OpenCV, image preprocessing, classification, object detection, OCR, model evaluation, and inference pipelines DevOps: Git, automated testing, CI/CD, infrastructure as code, release management, and environment management Containers: Docker and Kubernetes or equivalent container platforms Security: Secure coding, vulnerability scanning, secrets management, IAM, encryption, audit logging, and compliance Monitoring: Application, database, pipeline, infrastructure, and AI-model observability Our client is a leading IT Industry, and we are currently interviewing to fill this and other similar contract positions. If you are interested in this position, please apply online for immediate consideration. Pyramid Consulting, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, colour, 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. By applying to our jobs you agree to receive calls, AI-generated calls, text messages, or emails from Pyramid Consulting, Inc. and its affiliates, and contracted partners. Frequency varies for text messages. Message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You can reply STOP to cancel and HELP for help. You can access our privacy policy here.

Job Description Job Description Client: M&T Bank Job #: 2881 Job Title: Data Solution Architect Location: Remote w/ travel to Buffalo, NY required every 4 to 6 weeks' (mandatory no exceptions); Travel & lodging expenses will be reimbursed Duration: 6 -month contract W2 Pay Rate: Up to $80.00/hr. target on W2 ONLY (there is some wiggle room w/ the rate BOE / $4.50 to $5.00/hr. W2 referral fee / these roles are not C2C or 1099 eligible) Note: No visa sponsorship/transfer legally authorized to work in the US without visa sponsorship/transfer now or in the future (actual visa card must be valid for the next 24 -months / No H1B or OPT) NOTES FROM MANAGER/REQUIRED SKILLS & EXP.: This posting is for a Data Solution Architect. Eastern/Central time zones required. Travel to Buffalo, NY or Wilmington, DE required once every 4-6 weeks on average. Candidate should have exceptional communication skills and hand on experience in designing, building, and solutioning data related solutions. Candidate should have previous experience as a solution architect and should be able to articulate tangible architecture artifacts that they have personally produced. Solution Architect for Data (someone who can get into the full details of data systems/design). Skill Set 1: Design scalable, secure, and governed data solutions across platforms Skill Set 2: Hands-on experience with modern data ecosystems, integration patterns, and analytics platforms Skill Set 3: Exceptional ability to translate complex technical concepts into clear business outcomes Can this role be fulfilled remotely? Yes Job Title: Data Solution Architect Location: Buffalo, New York (Preferred) / Remote (Will be expected to travel to Buffalo, NY every 4-6 weeks with Monday through Thursday in office; travel expense reimbursed by M&T) Department: Enterprise Architecture Reports To: Enterprise Architect for Data, Analytics & AI Job Summary The Data Solution Architect is responsible for designing and delivering enterprise-grade data platforms and solutions that enable advanced analytics and business intelligence. This role requires deep expertise in data engineering, cloud-native architecture, and modern data technologies. The architect will work closely with engineering, product, and compliance teams to build secure, scalable, and regulatory-compliant data solutions. All solutions must align with the principles, standards, and reference architectures established by the Enterprise Architecture function, ensuring consistency, interoperability, and strategic fit across the organization. Key Responsibilities Solution Architecture: Architect and deliver cloud-based data platforms (e.g., Azure Data Lake) and scalable data pipelines using technologies such as Databricks, Kafka, etc. ETL/ELT Frameworks: Develop and implement ETL/ELT frameworks for ingesting, transforming, and integrating data from diverse sources, including legacy financial systems, SaaS platforms, and real-time data streams. Data Platform Deployment: Design and oversee deployment of data warehouses, lakehouses, and analytics sandboxes to support business intelligence, machine learning, and reporting needs inclusive of Power BI and Snowflake. Data Governance: Define and enforce data governance, metadata management, and data quality standards in accordance with Enterprise Architecture guidance and regulatory requirements. Enterprise Architecture Collaboration: Collaborate with Enterprise Architecture to ensure all solutions adhere to architectural standards, reference models, and technology roadmaps. Technology Evaluation: Lead technical evaluations and proof-of-concept projects for emerging data technologies (e.g., real-time analytics, data mesh, AI/ML platforms). Technical Documentation: Produce deliverables such as architecture diagrams, data flow maps, security models, and technical documentation for solution handoff and operational support. Agile/DevOps Leadership: Guide Agile/DevOps teams in implementing CI/CD pipelines, automated testing, and infrastructure-as-code for data solutions. Expected Skills Data engineering platforms, big data technologies, and cloud-native development (microservices, Kubernetes). API design (REST) and integration tools (ETL/ELT). Stakeholder communication (technical and non-technical audiences). Leadership in Agile/DevOps environments. Analytical problem-solving for complex data systems. Project management: proficiency in tools like Jira; familiarity with SDLC and CI/CD pipelines. Expected Knowledge Foundational Understanding: Data modeling, data pipeline orchestration, data quality management, metadata management, and data lifecycle. Data Platforms: Data lakes, warehouses, and lake house architectures; distributed systems and cloud data services. Data Engineering: ETL/ELT processes, real-time and batch data processing, data integration, and automation. Financial Systems: Payment networks, liquidity management, and settlement processes (as relevant to data flows). Regulatory Landscape: Global data privacy regulations (GDPR, CCPA) and compliance tools. Security: Data encryption, access controls, and penetration testing methodologies. Qualifications Education: Bachelor's/Master's in Computer Science, Engineering, or related field. Certifications: AWS/Azure Solutions Architect, Certified Data Engineer, or similar Experience: 5 years in solution architecture or technical implementation, with 2 years in data engineering or enterprise data platforms. Proficient in system design, integration, and implementation across multiple technology domains. Proven track record in deploying scalable financial systems (e.g., payment gateways, digital wallets, stablecoin or cryptocurrency systems preferred) Hands-on experience with cloud platforms (Azure/AWS/GCP), containerization (Kubernetes), and DevOps practices. Excellent communication, collaboration, and critical thinking skills. Understanding of financial regulations, compliance, and security standards. Expected Deliverables End-to-end solution architectures for data platforms, including detailed diagrams, technology stack specifications, and integration patterns. ETL/ELT pipeline designs and implementation plans for onboarding new data sources and modernizing legacy systems. Data governance frameworks, including policies for data quality, lineage, and access control, aligned with Enterprise Architecture standards. Technical documentation packages: architecture blueprints, operational runbooks, and security protocols. Prototypes and proof-of-concept implementations demonstrating new data engineering capabilities (e.g., streaming analytics, automated data quality checks). Performance benchmarks and scalability assessments for deployed solutions. Risk mitigation plans, including security audit findings and disaster recovery strategies. This role combines technical depth with strategic vision to build data platforms that bridge traditional finance and modern analytics ecosystems. The ideal candidate will balance innovation with operational rigor to deliver secure, compliant, and user-centric data solutions. Join M&T Bank and be part of a team that is shaping the future of banking technology.

Job Description Job Description TITLE: Sr. ERP Enterprise Data Architect Direct Hire No Sponsorship Hybrid - Ft. Worth, Texas Our client is investing significantly in the modernization of its enterprise data ecosystem and is seeking a Sr. ERP Enterprise Data Architect to help shape that transformation. The successful candidate will have broad influence over how enterprise data is architected, governed, secured, integrated, and consumed across the organization. The ideal candidate understands big-picture strategy and has technical depth to remain close to the technology. Requirements: 7-10+ years of progressive technology experience with approximately 3-5+ years in data architecture, enterprise architecture or senior-level data engineering. ERP implementation experience combined with data architecture and integration. Strong experience designing enterprise-scale data architectures within AWS. Deep knowledge of data modeling, schema design, data lineage, governance and enterprise data-management principles. Hands-on architectural experience with AWS technologies such as Redshift, Glue, DynamoDB, S3, Lambda, EMR and Lake Formation. Strong understanding of modern data lake, data warehouse and cloud data-platform architecture. Comfortable at both defining the enterprise strategy and technical architecture levels. Experience designing scalable data integration and pipeline patterns. Understanding of real-time, batch and event-driven data architectures. Ability to architect for data security, access control, encryption, governance and regulatory requirements. Experience collaborating across data engineering, application development, cybersecurity, integration and cloud infrastructure teams. Strong communication skills with the ability to translate complex technical concepts into clear architectural direction for both technical and business stakeholders. Demonstrated ability to influence technology decisions across teams without relying solely on direct authority. Bachelor's degree in Computer Science, Information Systems, Engineering or a related discipline, or an equivalent combination of education and relevant professional experience. Responsibilities: Own and evolve conceptual, logical and physical enterprise data models across core business domains. Lead architecture for AWS-based enterprise data platforms utilizing technologies such as AWS Glue, Redshift, Lambda, EMR, Lake Formation, DynamoDB and S3. Establish enterprise data architecture standards, taxonomy, naming conventions, governance practices, retention policies and data-lineage frameworks. Define scalable architecture patterns supporting analytical, operational and integration workloads. Partner with cybersecurity teams to establish appropriate identity, access control, audit logging and encryption strategies across data platforms. Design architectural patterns supporting real-time, batch and event-driven integrations utilizing technologies such as Kinesis, Kafka and EventBridge. Guide the architecture of enterprise analytical ecosystems supporting business intelligence, machine learning, advanced analytics and reporting. Partner with platform engineering teams on infrastructure automation, Infrastructure as Code (IaC), CI/CD and data-pipeline observability. Collaborate with application and integration teams to improve data consistency and interoperability across enterprise systems. Lead architecture reviews and provide technical direction for large-scale programs and strategic data initiatives. Evaluate emerging AWS data and analytics technologies and make recommendations regarding adoption and implementation. Mentor data architects and engineers while helping mature the organization's enterprise data architecture capabilities. Particularly Valuable Experience Experience in several of the following areas would be highly desirable but not a hard requirement: AWS Step Functions and/or Apache Airflow Kafka, Kinesis or other event-streaming technologies Hybrid cloud/on-premise data connectivity Machine learning and advanced analytics data environments Infrastructure as Code and automated cloud deployment Building or maturing enterprise data architecture standards and practices AWS Certified Solutions Architect - Professional or AWS data/analytics credentials Comprehensive Benefits Provided

Job Description Job Description This job is hybrid in Phoenix,AZ Our direct client has an opening for a Solution Architect - 9150 This position is up to 6 months, with the option of extension, and is located in Phoenix, AZ. If you are interested, please submit the following: YOUR CURRENT RESUME YOUR HOURLY RATE We can work w2 or corp to corp. Solution Architect - Data The Solution Architect - Data is responsible for contributing to the design, modernization, and optimization of enterprise-scale data systems, as well as the maintenance and operations strategy for CHP. This role involves designing and implementing data systems that organize, store, and manage data within our cloud data platform. The architect will perform continuous maintenance and operations work for CHP in the cloud environment. They will review and analyze CHP's data infrastructure, plan future database solutions, and implement systems to support data management for CHP users. Additionally, this role is accountable for ensuring data integrity, making sure the CHP team adheres to data governance standards to maintain accuracy, consistency, and reliability across all systems. The architect will identify data discrepancies and quality issues, and work to resolve them. This position requires a strong blend of architectural leadership, technical depth, and the ability to collaborate with business stakeholders, data engineers, machine learning practitioners, and domain experts to deliver scalable, secure, and reliable AI-driven solutions. The ideal candidate will have a proven track record of delivering end-to-end ETL/ELT pipelines across Databricks, Azure, and AWS environments. Key Responsibilities • Design scalable data lake and data architectures using Databricks and cloud-native services. • Develop metadata-driven, parameterized ingestion frameworks and multi-layer data architectures. • Optimize data workloads and performance. • Define data governance frameworks for CHP. • Design and develop robust data pipelines. • Architect AI systems, including RAG workflows and prompt engineering. • Lead cloud migration initiatives from legacy systems to modern data platforms. • Provide architectural guidance, best practices, and technical leadership across teams. • Build documentation, reusable modules, and standardized patterns. Required Skills and Experience • Strong expertise in cloud platforms, primarily Azure or AWS. • Hands-on experience with Databricks. • Deep proficiency in Python and SQL. • Expertise in building ETL/ELT pipelines and ADF workflows. • Experience architecting data lakes and implementing data governance frameworks. • Hands-on experience with CI/CD, DevOps, and Git-based development. • Ability to translate business requirements into technical architecture. Technical Expertise Programming: Python, SQL, R Big Data: Hadoop, Spark, Kafka, Hive Cloud Platforms: Azure (ADF, Databricks, Azure OpenAI), AWS Data Warehousing: Redshift, SQL Server ETL/ELT Tools: SSIS Required Educational Background • Bachelor's degree in Computer Science, Information Technology, Information Systems, Engineering, or a related field. • 6+ years of experience in data engineering or .NET development.

Job Description Job Description The Performance & Insights Engineer sits within SM Energy's Enterprise Performance & Insights team, reporting into the Chief Operating Officer organization, and works at the intersection of petroleum engineering, data engineering, and executive decision support. This role translates complex subsurface, operational, and financial data into high-impact analyses, models, and executive-ready deliverables that inform Investor Relations (IR) and Board of Directors (BOD) communications and advance critical strategic initiatives. Combining a working command of operational and asset engineering fundamentals with full-stack data wrangling and coding capability and modern AI-assisted workflows, the engineer independently frames ambiguous business problems, builds scalable end-to-end analytical solutions, and communicates insights persuasively to senior leadership. Operates under limited review while handling assignments of broad scope and complex difficulty; may mentor less experienced analysts and engineers and supervise their technical work. Essential Roles and Responsibilities Translate complex operational, development, and financial business problems into end-to-end analytical solutions - from data acquisition and pipeline through model, visualization, and executive-ready deliverable. Build, maintain, and optimize data pipelines, queries, and analytics data views across production, reservoir, financial, and capital-planning domains using SQL and Python; design and test scripts, stored procedures, functions, and views. Deliver executive and Board-ready artifacts through an agentic, AI-assisted workflow - directing tools such as Claude to build self-contained HTML dashboards, branded decks, and models from a spec, then refining them while retaining judgment over accuracy and design. Understanding of production and reservoir engineering fundamentals - decline curve analysis (DCA), rate/pressure transient analysis (RTA/PTA), volumetrics, EURs, artificial lift, and production optimization - to QA/QC data and pressure-test analytical results for physical reasonableness. Develop capital-efficiency, production-performance, operational KPIs, and economic metrics and models that support budgeting, forecasting, and strategic decision-making across operating regions. Design and produce executive-facing reporting - BOD slides, IR materials, and interactive dashboards - built to SM Energy brand standards. Leverage AI tools (e.g., large language model assistants such as Claude) to accelerate code development, data QA/QC, documentation, and analysis, applying sound engineering judgment to validate and stress-test AI-assisted output. Develop correlations between geological, completion, operational, and financial variables and well- and asset-level performance. Perform ad-hoc analyses; troubleshoot data-quality issues across the business; proactively identify potential issues and recommend solutions. Serve as a liaison across Operations, Finance, IR, Reservoir/Asset teams, and IT/Data - bridging deeply technical work and business audiences. Monitor production, capital, and financial data for discrepancies and opportunities; recommend operational and process improvements. Contribute to data governance, code documentation, change-release process, and best practices; educate others in support of a data- and AI-first culture. Manage and engage in multiple initiatives simultaneously; independently prioritize tasks and eliminate roadblocks to meet target deadlines. Conduct business with the highest ethical standards; demonstrate decision-making that ensures the safety of all people associated with SM facilities. Other duties as assigned. Role-Specific Technical Knowledge & Skills Petroleum Engineering. Working command of production operations, artificial-lift applications, and fundamental reservoir engineering disciplines - decline curve analysis, rate/pressure transient analysis, volumetrics, recoveries, EURs, and recovery factors. Understanding of unconventional resource plays across multiple basins/operating regions and familiarity with reserves, economics, AFE, and capital-planning workflows. Ability to identify limitations and ranges of certainty in a data set and to relate reservoir, completion, and operational characteristics to well performance. Data Engineering & Analytics. Advanced ability to wrangle, pre-process, and feature-engineer data and to connect data from disparate sources to surface insights, data-quality issues, and variable correlations. Sound applied-statistics foundation; competence with machine-learning concepts and frameworks a plus. End-to-end pipeline design that is cost-effective and scalable; strong code documentation and change-management discipline. AI-Augmented Delivery. Ability to integrate AI tools into daily delivery to compress cycle time while retaining engineering ownership of correctness - treating AI output as a draft to be verified, not a final answer. Understands data-security and data-privacy implications of AI-assisted and cloud-based workflows and accounts for them appropriately. Computer/Software Applications Programming & Analytics: Advanced SQL and Python (pandas, numpy, and related data ecosystem); R or comparable a plus. Data Platforms & Architecture: Data virtualization via Denodo; Snowflake and/or Databricks; Palantir Foundry; relational database design; ETL/ELT (dbt, SSIS); cloud environments (Azure, AWS). Visualization & Reporting: Governed enterprise BI (Power BI, Spotfire, or Tableau) for refreshing dashboards, plus bespoke interactive tools built as self-contained HTML dashboards (D3, Plotly, Recharts) that run anywhere without a license or server. Advanced PowerPoint and Excel for executive and Board deliverables, produced to SM Energy brand standards. Development Tools: Git/GitHub, modern IDEs (VS Code, PyCharm), notebooks (Jupyter), and fast dependency/environment management (uv, Poetry, conda). Comfortable in the agentic developer loop - coding assistants such as Claude Code, Cursor, or GitHub Copilot working inside the IDE/terminal, not used only as a side chat. Agentic Delivery: Fluent in AI-assisted artifact creation - directing agentic tools (e.g., Claude) to build branded HTML dashboards, PowerPoint decks, and Excel models end to end from a specification, then refining them iteratively. Applies SM's visual standards programmatically ("brand-as-code") so output is board-ready by default, and exercises judgment over layout, data integrity, and narrative clarity rather than accepting first-pass output. AI-Augmented Development: Fluent in an AI-native analytics workflow - uses LLM assistants (e.g., Claude) and agentic tools to accelerate development, QA/QC, refactoring, and documentation, always validating output against engineering judgment. Can leverage the Model Context Protocol (MCP) to connect AI agents securely to enterprise data and tools (e.g., querying Denodo or Snowflake, drafting Office deliverables) and platform-native AI such as Snowflake Cortex and Power BI Copilot, keeping data security and governance front of mind. Petroleum Engineering Software: Aries, Wellview, and Spotfire; exposure to RTA/PTA and production-analysis tools; reservoir simulation and frac models a plus. Education Bachelor's degree required in Petroleum, Chemical, or Mechanical Engineering; Data Science; Computer Science; Statistics; or a related quantitative field. A dual foundation in engineering and computing/data is strongly preferred. Advanced degree a plus. Typical Experience Minimum of 6 years of relevant experience. Experience should span both petroleum engineering (production/operations, and/or reservoir) and hands-on data/analytics development. Demonstrated delivery of executive- or Board-facing analytical work is strongly preferred. SM Energy offers competitive compensation and benefits programs which include, but are not limited to, variable pay, health care coverage, retirement plan, protection coverage, time off and leave programs, training and development opportunities and a range of allowances connected to specific work situations. Details are available at Careers SM Energy Company (SM) (). Applications will be accepted on an ongoing basis until the position is filled.

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 Join Sky Solutions, LLC - Pioneering Digital Transformation Excellence! Sky Solutions is a trusted partner in government contracting, empowering federal agencies with cutting-edge IT solutions. Our expertise spans AI-first enablement, delivering innovative solutions and advanced cybersecurity, fortifying digital ecosystems against emerging threats and digital transformation through low-code/no-code development, cloud solutions, and agile methodologies. We simplify complex processes and deliver breakthrough results for federal clients across healthcare, financial services, and national security. Technical Architect - Enterprise Modernization, AI & Automation Location: Tysons Corner, VA (Hybrid) Employment Type: Full-Time Position Overview Sky Solutions LLC is seeking a highly experienced Technical Architect to support a federal digital transformation initiative associated with the DOJ Office of Justice Programs (OJP). The ideal candidate will lead enterprise architecture, application modernization, cloud-native solution design, and the adoption of AI-driven automation technologies to improve mission outcomes and operational efficiency. This role requires a strategic and hands-on technology leader who can translate complex business and mission requirements into secure, scalable architecture roadmaps while guiding the adoption of emerging technologies across enterprise federal environments. Key Responsibilities Design and oversee modern, cloud-native, microservices-based, low-code/no-code, and API-first architectures that enable digital transformation, scalability, and interoperability with federal systems and external partners. Lead enterprise application modernization initiatives, including legacy system transformation, cloud migration, workflow orchestration, and integration modernization. Champion the adoption of Artificial Intelligence (AI), Machine Learning (ML), Generative AI, and Intelligent Automation, including Robotic Process Automation (RPA), to improve mission outcomes and enable data-driven decision-making. Evaluate and architect AI-enabled solutions using cloud platforms such as AWS, Microsoft Azure, and Google Cloud Platform (GCP), as well as federated and on-premises model deployment frameworks. Conduct proofs of concept (PoCs), pilots, and technical assessments for emerging technologies, including Generative AI copilots, AI-driven analytics, and intelligent process automation. Identify opportunities to apply AI and low-code/no-code platforms to automate business processes, modernize legacy environments, and improve operational efficiency. Develop enterprise architecture strategies, target-state architectures, technology roadmaps, reference architectures, and implementation plans aligned with business objectives. Collaborate with business leaders, government stakeholders, and IT teams to translate mission needs into actionable technical solutions. Establish architecture standards, integration patterns, security principles, and technology governance practices across development teams. Ensure architecture incorporates security, privacy, accessibility, interoperability, performance, scalability, and maintainability requirements. Provide technical leadership across engineering, DevSecOps, data, cybersecurity, and application development teams. Assess emerging technologies, architectural risks, and implementation trade-offs, providing recommendations to executive, technical, and mission stakeholders. Required Qualifications Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline; equivalent experience may be considered. 10+ years of progressive experience in enterprise architecture, solution architecture, or large-scale technology solution design. At least 5 years of experience leading large-scale application modernization, AI/automation, or digital transformation initiatives in federal government environments. Demonstrated experience designing enterprise-scale architectures involving cloud-native applications, microservices, APIs, and distributed systems. Experience developing architecture roadmaps and translating innovation strategies into actionable implementation plans. Experience evaluating and implementing AI/ML, Generative AI, intelligent automation, or workflow automation solutions. Experience with one or more major cloud platforms: AWS, Microsoft Azure, or GCP. Understanding of enterprise integration, API management, data architecture, identity and access management, and secure software development. Demonstrated ability to communicate complex technical concepts to executive leadership, technical teams, and mission stakeholders. Strong architectural governance, technical decision-making, problem-solving, and stakeholder management skills. Preferred Qualifications Experience supporting DOJ, OJP, or other federal civilian agency programs. Familiarity with grants-management, case-management, or workflow-intensive enterprise platforms. Experience with low-code/no-code platforms, business process management, workflow orchestration, and RPA technologies. Experience designing AI-enabled architectures, including Generative AI applications, enterprise copilots, retrieval-augmented generation (RAG), and AI-driven analytics. Familiarity with federated AI architectures, hybrid cloud deployments, and on-premises model hosting. Knowledge of federal cybersecurity and compliance frameworks, including applicable NIST standards, FedRAMP requirements, and Section 508 accessibility. Experience with responsible AI practices, including data protection, model governance, access controls, and AI output validation. Relevant cloud, enterprise architecture, AI, or automation certifications. Success in This Role Delivery of practical, secure, and scalable enterprise architecture roadmaps. Successful modernization of legacy applications and business processes. Effective adoption of AI-enabled capabilities and intelligent automation where they provide measurable value. Improved interoperability, operational efficiency, maintainability, and alignment with federal mission objectives. Compensation : The expected compensation range for this position is $118,890 - $201,014 annually. Compensation is determined in good faith and may vary based on job-related factors, including relevant experience, skills, education, certifications, clearance level, labor category alignment, contract requirements, work location, internal equity, and business needs. The posted range reflects the Sky's reasonable estimate at the time of posting and does not guarantee a specific salary or rate. Final compensation will be determined based on the selected candidate's qualifications and applicable contractual and business considerations. Sky Solutions Benefits & Culture at a Glance Healthcare & Wellness Medical, dental, and vision coverage tailored to your needs. Supplemental options like life insurance, disability, HSA/FSA available. Time Off & Work-Life Balance Starting at 15 PTO days per year, increasing with tenure. Plus 11 paid holidays to recharge and spend time with loved ones. Professional Growth & Development Annual education stipend. Access to thousands of online courses. Formal mentorship programs for career advancement. Inclusive Culture "One Team" mentality focused on collaboration and belonging. Recognized as a Great Place to Work for six years straight. To learn more about life at Sky Solutions, visit our Careers page: Careers - Sky Solutions

Director AI Engineer 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. Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Make high judgment build-vs-buy decisions across 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. Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI. Translate the enterprise AI strategy into portfolio-level execution plans across multiple product areas, balancing innovation with delivery discipline Scale AI engineering practices across teams through shared infrastructure, reusable components, and unified observability and governance frameworks Establish enterprise standard for Responsible AI, including fairness metrics, model evaluation protocols, documentation requirements, and audit readiness Partner with research, compliance, and enterprise risk teams to ensure deployed systems meet emerging ethical and regulatory standards 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 get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example 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 8 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 6 years of experience developing AI and ML algorithms or technologies At least 3 years of people leadership experience Preferred Qualifications: 5+ years of experience managing and leading an engineering team 7+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) 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 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 Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience building and leading multi-team AI organization delivering multiple enterprise products or capabilities concurrently Proven ability to expand and execute long-term AI platform strategies aligned to enterprise priorities and regulatory frameworks Experience establishing cross-functional operating rhythms and review cadences (OKRs, AI governance councils, quarterly reviews) Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 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. Cambridge, MA: $269,100 - $307,200 for Director, AI Engineer McLean, VA: $269,100 - $307,200 for Director, AI Engineer New York, NY: $293,600 - $335,100 for Director, AI Engineer San Francisco, CA: $293,600 - $335,100 for Director, AI Engineer San Jose, CA: $293,600 - $335,100 for Director, AI Engineer 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. . click apply for full job details

Director AI Engineer 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. Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Make high judgment build-vs-buy decisions across 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. Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI. Translate the enterprise AI strategy into portfolio-level execution plans across multiple product areas, balancing innovation with delivery discipline Scale AI engineering practices across teams through shared infrastructure, reusable components, and unified observability and governance frameworks Establish enterprise standard for Responsible AI, including fairness metrics, model evaluation protocols, documentation requirements, and audit readiness Partner with research, compliance, and enterprise risk teams to ensure deployed systems meet emerging ethical and regulatory standards 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 get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example 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 8 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 6 years of experience developing AI and ML algorithms or technologies At least 3 years of people leadership experience Preferred Qualifications: 5+ years of experience managing and leading an engineering team 7+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) 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 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 Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience building and leading multi-team AI organization delivering multiple enterprise products or capabilities concurrently Proven ability to expand and execute long-term AI platform strategies aligned to enterprise priorities and regulatory frameworks Experience establishing cross-functional operating rhythms and review cadences (OKRs, AI governance councils, quarterly reviews) Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 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. Cambridge, MA: $269,100 - $307,200 for Director, AI Engineer McLean, VA: $269,100 - $307,200 for Director, AI Engineer New York, NY: $293,600 - $335,100 for Director, AI Engineer San Francisco, CA: $293,600 - $335,100 for Director, AI Engineer San Jose, CA: $293,600 - $335,100 for Director, AI Engineer 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. 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