227 jobs found

Please note, this position is designated as flexible, which means the selected candidate may be required to report to the assigned office in Greensboro, NC at least part of the time each week. Technical Summary: The IT Operations Entra team is responsible for the engineering, administration, and continuous improvement of Microsoft Entra services that provide enterprise cloud identity, authentication, authorization, and access management capabilities across the organization. This senior technical role serves as a subject matter expert for Microsoft Entra services and is responsible for leading the delivery, modernization, and ongoing evolution of core identity capabilities, including hybrid identity synchronization, Microsoft Entra Connect, authentication services, privileged access management, role-based access control, enterprise applications, and application identities. The position provides technical leadership for the engineering, implementation, administration, and operational sustainment of Microsoft Entra services across multiple tenants, while contributing to platform standards, automation, and operational best practices. This role partners closely with Azure Platform, IAM, Security, Microsoft 365, and application teams to ensure secure, scalable, and reliable identity services while advancing platform capabilities and operational excellence across the enterprise. Job Summary: This senior level individual contributor is primarily responsible for serving as the lead technical expert across project teams, setting technical direction across technical solutions, and overseeing all IT systems. Essential Responsibilities: Drives the execution of multiple work streams by identifying customer and operational needs; developing and updating new procedures and policies; gaining cross-functional support for objectives and priorities; translating business strategy into actionable business requirements; obtaining and distributing resources; setting standards and measuring progress; removing obstacles that impact performance; guiding performance and developing contingency plans accordingly; solving highly complex issues; and influencing the completion of project tasks by others. Practices self-leadership and promotes learning in others by soliciting and acting on performance feedback; building collaborative, cross-functional relationships; communicating information and providing advice to drive projects forward; adapting to competing demands and new responsibilities; providing feedback to others, including upward feedback to leadership; influencing, mentoring, and coaching team members; fostering open dialogue amongst team members; evaluating and responding to the strengths and weaknesses of self and unit members; and adapting to and learning from change, difficulties, and feedback. Leads a team of IT consultants in the development of requirements, for process or system solutions which may span multiple business domains by leveraging partnerships with stakeholders and appropriate IT teams (for example, Solutions Delivery, Infrastructure, Enterprise Architecture). Leverages multiple business requirements gathering methodologies to identify business, functional, and non-functional requirements (for example, SMART) across the enterprise. Leads and oversees the development and documentation of comprehensive business cases to assess the costs, benefits, ROI, and Total Cost of Ownership (TCO) of highly unique or complex solution proposals. Leads the evolution of applications, systems, and/or processes to a desired future state by translating how current processes impact business operations across the enterprise. Leads teams of IT Consultants in the mapping of current state against future state processes. Defines the impact of requirements on upstream and downstream solution components. Provides insight and influence to executive management and business leaders on how to integrate requirements with current systems and business processes across the enterprise. Reviews, evaluates, and prioritizes value gaps and opportunities for process enhancements or efficiencies. Leads solution design by translating requirements into workable business solutions and leading in design sessions with IT teams. Recommends and advocates for additional data and/or services needed to address key business issues related to process or solutions design. Leads the evaluation of third-party vendors as directed. Drives continuous process improvement by leading the development, implementation, and maintenance of standardized tools, templates, and processes across the enterprise. Recommends and advocates for regional and national process improvements which align with sustainable best practices, and the strategic and tactical goals of the business. Minimum Qualifications: Bachelors degree in Business Administration, Computer Science, CIS or related field and Minimum ten (10) years experience in IT consulting, business analysis, or a related field. Additional equivalent work experience may be substituted for the degree requirement.

Job Overview: Pay Range: $65hr - $70hr Requirement/Must Have: In-depth hands-on experience working with Windows Server in hybrid environments (on-premises and cloud). Demonstrated ability to translate user requests, provide technical support and communicate effectively. In-depth hands-on experience with OS upgrades, patch installation and testing. In-depth hands-on experience with scripting utilities (PowerShell) and Windows server scripting to accomplish centralized tasks. In-depth experience performing regular patching and updates to ensure system security and stability. Experience overseeing backup operations and recovery processes in mission critical environments. In-depth experience planning and executing server migrations, including moving workloads from on premises to the cloud. In-depth experience working in an environment that utilizes multiple frameworks/technologies including .NET, Java, SQL/Oracle, Microsoft Dynamics, etc. In-depth experience providing server-level support and troubleshooting issues for production applications. In-depth experience managing vulnerability server and application remediation. Experience with tools like SCCM for automated patch management & deployment. Experience crafting disaster recovery (DR) plans to ensure minimal downtime and prevent data loss. Strong networking knowledge - including understanding OSI layer functionality and network protocols. Ability to work with cross-functional teams to address infrastructure needs and support application deployment. Responsibilities: Administer, maintain, and optimize Windows Server environments across on-premises and cloud-based infrastructure. Perform OS upgrades, patch installation, testing, and ongoing system updates to ensure reliability and security. Develop and use PowerShell scripts and other automation tools to execute centralized and repetitive tasks efficiently. Lead and execute server migrations, including transitioning workloads from on-premises systems into cloud platforms. Implement and maintain security configurations for servers, including endpoint protection, access control, and hardening standards. Conduct vulnerability remediation for servers and applications to maintain security compliance. Work with security tools and processes to ensure consistent protection and monitoring. Manage patching cycles and use SCCM or similar platforms for automated patch deployment and reporting. Maintain ongoing monitoring and performance assessment of infrastructure services to identify and resolve issues proactively. Oversee routine backup operations and support recovery processes for mission-critical systems. Develop, refine, and support Disaster Recovery (DR) strategies to minimize downtime and protect data integrity. Provide advanced server-level support for enterprise applications using .NET, Java, SQL, Oracle, Microsoft Dynamics, and warehouse technologies. Troubleshoot high-impact production issues across hybrid infrastructure and middleware layers. Apply deep knowledge of OSI model layers and networking protocols to diagnose connectivity and application issues. Collaborate with cross-functional teams to support application deployments and infrastructure enhancements. Translate business or user requests into actionable technical solutions and communicate effectively. Work closely with the IT Portfolio Manager and Infrastructure & Operations teams to align engineering efforts with organizational needs. Nice to Have: Have achieved Microsoft-focus certifications such as Azure Administrator Associate, Windows Server Hybrid Administrator Associate, etc. Has achieved network focused certifications such as Network+, CCNA, etc. Benefits Our Benefits Include: Medical, Dental, and Vision Insurance 401(k) Retirement Plan Health Savings Account (HSA) Disability Insurance (Short-Term and Long-Term) Life and AD&D Insurance Paid Sick Leave (where required by applicable state or local law) Supplemental Insurance Plans Identity Theft Protection Pet Insurance Employee Wellness Programs Employee Assistance Program (EAP) Career Growth and Professional Development Opportunities Disclaimer: Benefits eligibility, accrual rates, and usage limits may vary based on employment status, length of service, and work location. Paid Sick Leave is provided in strict accordance with applicable state and municipal mandates. Cynet Systems Inc. reserves the right to modify, amend, or terminate any benefit plans at any time in accordance with applicable laws. About Cynet Systems Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading technology staffing and workforce solutions company serving Fortune 500 companies, government agencies, and enterprise organizations across the United States and Canada. We deliver agile, scalable talent solutions across IT, engineering, life sciences, clinical, and professional staffing, powered by a high-performing recruitment engine operating across North America and Asia. As a nationally and locally certified Minority Business Enterprise (MBE), Cynet Systems is committed to helping organizations build high-performing teams while empowering professionals to grow rewarding careers. Our organization is certified to ISO 9001, ISO 14001, ISO 27001, and SOC 2 Type II standards, reflecting our commitment to quality, security, operational excellence, and customer success.

Position: Cloud DevSecOps Engineer IV Location: Birmingham, AL Duration: 6 months Job ID: 178667 Job Overview: The Cloud DevSecOps Engineer IV contributes to the advancement of cloud strategy by developing, communicating, and implementing robust and secure cloud continuous integration and continuous delivery (CI/CD) pipelines. This role collaborates closely with stakeholders to create fully automated pipelines that align with current DevSecOps best practices. Responsibilities: Partner with engineers and IT staff to orchestrate code builds, quality and security analyses, deployments, and automated testing through CI/CD pipelines. Translate business needs into technology solutions. Model release candidate CI/CD pipelines to communicate the states and steps necessary for application and service release candidates. Design and develop fully autonomous CI/CD pipelines for cloud deployments, including automation of infrastructure services and application build and deployment. Ensure all pipeline components follow best software engineering practices, including automated tests and infrastructure tests. Research new technologies to improve efficiency and effectiveness. Implement scalable CI/CD platforms to support high change volumes and fast feedback. Complete project work and contribute to the technical direction of various objectives. Automate operational activities and tasks. Respond to performance issues identified by alerts and reported incidents related to CI/CD platforms. Build tools to reduce errors and improve customer experiences. Troubleshoot production issues and ensure pipelines and infrastructure provide clear documentation and metrics for root cause analysis. Develop and test Ansible Playbooks, Terraform Scripts, and Packer Scripts to establish immutable infrastructure. Collaborate with Enterprise Architecture, Information Security (InfoSec), Software Delivery, and Quality Assurance teams to enable cloud automation. Act as a resource and mentor for colleagues with less experience. Qualifications: High School Diploma or GED and ten (10) years of related post-secondary education and/or experience in Information Security or Information Technology. Preferences: Six (6) years of relevant DevSecOps experience. AWS DevOps certification or Azure DevOps certification. Experience in building and deploying cloud-native applications, such as OpenShift and Azure Kubernetes Service (AKS). Experience in observing real-time metrics in pipelines and deployment strategies, including Blue/Green and Canary Deployment. Experience with AWS or Azure cloud technologies. Experience interfacing with secrets management solutions like HashiCorp Vault. Familiarity with implementing Chaos engineering principles in pipelines to identify weak links and suggest solutions. Familiarity with testing tools for automation and integration into CI/CD pipelines. Proficiency in developing pipelines as code using YAML specs and Ansible Playbooks. Skills and Competencies: Excellent communication skills and ability to mentor developers and team members in DevSecOps practices. Strong knowledge of cloud infrastructure, networking services, and architectural patterns, including virtual machines, managed infrastructure, containers, serverless, database services, security services, and application services. Proficiency in Python programming language. Understanding of Shift Left principles and facilitation technologies. Working knowledge of Jenkins, Azure DevOps, Ansible, Terraform, Packer, Git, and ServiceNow. About PTR Global: PTR Global is a leading provider of information technology and workforce solutions. PTR Global has become one of the largest providers in its industry, with over 5000 professionals providing services across the U.S. and Canada. For more information visit At PTR Global, we understand the importance of your privacy and security. We NEVER ASK job applicants to: Pay any fee to be considered for, submitted to, or selected for any opportunity. Purchase any product, service, or gift cards from us or for us as part of an application, interview, or selection process. Provide sensitive financial information such as credit card numbers or banking information. Successfully placed or hired candidates would only be asked for banking details after accepting an offer from us during our official onboarding processes as part of payroll setup. Pay Range: $70 - $75/hr. W2. The specific compensation for this position will be determined by several factors, including the scope, complexity, and location of the role, as well as the cost of labor in the market; the skills, education, training, credentials, and experience of the candidate; and other conditions of employment. Our full-time consultants have access to benefits, including medical, dental, vision, and 401K contributions, as well as PTO, sick leave, and other benefits mandated by applicable state or localities where you reside or work. If you receive a suspicious message, email, or phone call claiming to be from PTR Global do not respond or click on any links. Instead, contact us directly at +1 . To report any concerns, please email us at During the hiring process, we may use artificial intelligence (AI) tools to assist in evaluating information related to your application. These tools may help analyze job-related qualifications or assist recruiters in reviewing applications and interview responses. AI-generated information is one factor considered in our hiring process. Final employment decisions are made by qualified hiring personnel and are not based solely on AI-generated recommendations.

Description: Position Summary The MFM IT team has a long history of delivering and maintaining core business systems in a mid-sized Property & Casualty insurance environment. As we expand our development team and adopt new AI development tools, we are making a deliberate investment in building this capability correctly from the start. As we begin to build agentic AI capabilities within our enterprise system, we are looking for an experienced engineer with strong knowledge of agentic AI systems to help guide this effort. The Senior Agentic AI Specialist will work closely with MFM's Principal Architect, who leads overall platform architecture, and partner with senior developers to design, implement, and improve agent-based solutions. This role will bring specialized expertise in areas where we are still developing depth, including agent orchestration, retrieval pipelines, LLM evaluation, and prompt design. This is an ongoing platform effort, not a one-time project. The work will evolve over time as we expand capabilities, integrate new tools, and improve system quality. Our core systems are built on a Microsoft/.NET stack. As we develop our agentic AI capabilities, we expect to leverage cloud-based tooling (likely within Azure) where appropriate. We are pragmatic about using the right tools for the problem, while maintaining alignment with our existing platform and operational requirements. At Midwest Family we value practical experience, clear thinking, and the ability to apply these skills in a real-world environment. Application Requirements Cover Letter and Resume: Please include the following in your cover letter A description of an AI or agent-based system you have worked on, including your role and how you evaluated quality Your approach to reducing incorrect or unsupported outputs An example of how you supported other developers or teams in adopting AI capabilities Your physical remote work location state Salary expectations Responsibilities: Platform Architecture & Evolution : Provide input into AI-related architecture decisions. Evaluate tools, models, and approaches, and make practical recommendations based on trade-offs and outcomes. Agent Lifecycle Management: Design, build, and maintain agents. Define prompts and configurations, support routing decisions, and monitor performance in production. RAG Pipeline Engineering: Improve retrieval quality by working with chunking strategies, embeddings, search methods, and metadata filtering. Support onboarding of new knowledge sources. Quality & Hallucination Reduction: Help reduce incorrect or unsupported outputs through system design, testing, and monitoring. Apply practical approaches across prompts, retrieval, and model behavior. Evaluation & Testing: Develop and maintain evaluation approaches to measure output quality, including relevance and accuracy. Support regression testing and identify failure patterns. Prompt Engineering: Create and maintain prompts for different agents. Diagnose unexpected behavior and develop reusable patterns where appropriate. Tool Integration: Support integration with internal systems and APIs. Help manage tool access and ensure reliable execution and error handling. Observability & Operations: Contribute to logging, tracing, and monitoring. Support analysis of system behavior, cost, and performance in production. Governance & Configuration: Work with configuration across agents, prompts, and models. Ensure changes are version-controlled and reviewed. Developer Support: Work with other developers to share knowledge, review designs, and establish consistent approaches. Research & Evaluation: Stay current with new models and tools. Evaluate them in a structured way and recommend adoption where appropriate. Requirements: Education & Certification College degree or Programming Certification (preferred) 5+ years of equivalent work experience Required Experience Experience building or working with AI/LLM-based systems in a production or near-production environment Strong understanding of agent-based patterns (ReAct, tool usage, etc.) Experience with retrieval-based systems (RAG), vector stores, or search pipelines Familiarity with evaluating non-deterministic system outputs Experience improving system quality through testing and iteration Strong software engineering skills required. Experience with Python, TypeScript, or C# preferred Ability to work across technologies and integrate AI solutions into an existing enterprise environment Preferred Experience Experience working with multiple LLM providers Familiarity with emerging tools and frameworks in the agentic AI space Experience integrating with enterprise systems and data sources Experience mentoring or supporting other developers Personal Attributes Strategic thinker with strong analytical and problem-solving skills Technically proficient with broad systems knowledge Excellent interpersonal, written, and verbal communication skills Self-directed, collaborative, and highly organized Customer-oriented and able to navigate high-pressure environments Flexible and adaptable in regards to learning and understanding new technologies. Exceptional organizational skills and ability to keep track of multiple projects at a time. Ability to conduct research into software-related issues and products. Technically proficient. Exceptional attention to detail. Ability to work both independently and in a team-oriented, collaborative environment. Work Conditions Remote work environment following core hours 8AM-5PM Central Time Overtime may be required to meet project deadlines or monitor system processes. Sitting for extended periods of time. Dexterity of hands and fingers to operate a computer keyboard, mouse, and other devices. Minimal travel will be required for the purpose of off-site software training and team meetings. Physically able to participate in virtual and in-person training sessions, presentations, and meetings. PI6a59fdda4e68-4236

Job Information Job Title D ata Architect Home Department: I nformation Technology Employment Status: Exempt; Full-time Schedule: Flexible Scheduling Opportunities Position Location: Remote/ Hybrid (commutable distance to home office in Fond du Lac, WI) This position offers flexible remote/hybrid work scheduling and we are targeting candidates who are located within the commutable greater Fond du Lac, WI area for infrequent in-person meeting events. Visit us at to learn more. Overview Protecting our policyholders' dreams, passions, and livelihoods has a direct impact on the communities we serve. We work towards excellence, conduct ourselves with high integrity, and take our work seriously, but not ourselves. Small Details. Big Difference. Find out how you can make a difference with a career at Society. Society Insurance is seeking an experienced Data Architect to join our IT team. The Data Architect leads the design and implementation of the enterprise data architecture, translating business and data strategy into scalable, governed, and high-performing data platforms and solutions. The role is accountable for delivering the data architecture vision and enabling execution of the data strategy, including data models, pipelines, platforms, and integration patterns that support analytics, reporting, and operational use cases. The Data Architect partners with business and IT stakeholders to ensure data is trusted, accessible, and aligned to enterprise architecture standards, while driving modernization and continuous improvement of data capabilities. About the Role Translates enterprise data strategy into architecture, platforms, and implementation roadmaps aligned to business and analytics needs. Engages with business and IT stakeholders to gather requirements and define end-to-end data architecture solutions. Defines and governs enterprise data architecture standards, including data models, pipelines, integration patterns, and platform design. Designs and builds scalable data platforms and pipelines (data lakes, warehouses, cloud platforms) to support analytics and reporting. Establishes and enforces data modeling standards (logical, physical, dimensional) across systems and domains. Designs and optimizes data ingestion, transformation, and integration patterns (ETL/ELT) to ensure reliable data movement across systems. Ensures data architecture supports data quality, lineage, metadata, and governance frameworks aligned to enterprise standards. Collaborates with architects and engineers to define architecture enablers, guide solution design, and support implementation. Works with data engineering and Agile teams to ensure architecture is implemented effectively across delivery cycles. Leads evaluation and selection of data technologies, tools, and platforms, including proof-of-concepts (POCs). Develops and maintains data architecture roadmaps, including modernization, consolidation, and performance optimization. Drives modernization of legacy data and reporting platforms to improve scalability, performance, and usability. Ensures alignment between data, application, and infrastructure architecture. Participates in Agile/PI Planning to align teams to a shared technical direction and standards. Acts as a technical expert and leader, mentoring teams and driving adoption of best practices across data architecture and engineering. About Yo u You are analytical and connect data across systems to support business insight and decision-making. You are creative and innovative and identifies better ways to organize, integrate, and govern data. You are driven by an underlying curiosity and desire to know more about things, people, or issues. You take ownership of challenges and drive improvements in architecture, standards, and processes. You quickly apply new knowledge, tools, and ideas to solve business and data challenges. You enjoy managing the efficiency, accuracy, and integrity of the work that you produce. You effectively prioritize work, manage multiple responsibilities, and meet deadlines. What it Will Take Bachelor's degree in computer science, engineering, or related field. 8+ years of experience in data architecture, data engineering, or data platform design. Strong experience designing and implementing data pipelines, data lakes, and data warehouses. Experience with cloud data platforms, (Azure Synapse, Data Factory, Fabric, Databricks, etc.) Deep understanding of data modeling, ETL/ELT patterns, and data integration. Experience implementing data architecture aligned to business and analytics needs. Strong collaboration skills across business, architecture, and engineering teams. Expertise in one or more of the following, but with versatility to grow in other areas: Microsoft stack of Data Tools & Technologies (SQL, SSIS, TSQL) Azure SQL Databases Azure Blob storage Azure App Services Microsoft Azure Synapse, Data Factory & Fabric Microsoft stack of Business Intelligence Tools (Power BI) Data Modeling (Idera ERStudio) Data Warehouse Design Data Analytics Concepts Strong organizational skills. Demonstrated success in managing and/or completing projects. SAFe Agile Delivery experience highly desirable. What Society Can Offer Comprehensive Benefits Package : Salary with bonus plan; health, dental, life, and vision insurance Retirement : Traditional or Roth 401(k) Defined Contribution Plan PLUS Profit-Sharing Plan Work-Life Balance : Company-paid holidays; flexible scheduling; PTO; telecommuting options Education : Career Coaching; company-paid courses; student loan and tuition reimbursement Community : Charitable Match; paid volunteer time; team sponsorships Wellness : Employee Assistance Program; wellness initiatives/rewards; health coaching; and more Society Insurance prohibits discrimination and harassment of any type against applicants and employees on the basis of race, color, religion, sex, national origin, age, handicap, disability, genetics, veteran status or military service, marital status or sexual orientation, gender identity or expression, or any other characteristic or status protected by federal, state or local laws. Society Insurance also provides reasonable accommodations to qualified individuals with disabilities in accordance with the requirements of the Americans with Disabilities Act and applicable state and local laws. PIc5b0b43690ba-1158

Description: CarShield is seeking an experienced Database Administrator to join its growing database team. In this role, you'll be responsible for administering and optimizing our SQL Server environment, ensuring the availability, performance, security, and reliability of critical databases that support our business. You'll work closely with developers and IT teams to implement high-availability solutions, troubleshoot production issues, maintain backup and disaster recovery strategies, and continuously improve database performance and operational efficiency. Administer and monitor SQL Server instances across our on-premises environment Manage Always On Availability Groups, including failover, replica health, and AG job synchronization Own backup/restore strategies and DR testing to ensure RTO/RPO targets are met Performance-tune queries and workloads via execution plans, DMVs, wait stats, and indexing Manage SQL Server security - logins, roles, permissions auditing, and least-privilege enforcement Respond to production incidents, diagnose root causes, and implement durable fixes Collaborate with developers to review schema changes and query patterns before they hit production Monitor and maintain SQL Agent jobs, including Change Data Capture (CDC) Requirements: 5+ years of SQL Server DBA experience in a production environment Hands-on experience administering Always On Availability Groups Strong grasp of performance tuning - execution plans, index strategy, wait statistics Solid understanding of SQL Server security, auditing, and access control Experience with backup/restore, DR planning, and failover procedures Must be able to work on-site in St. Peters, MO 5 days/week Bachelor's in Computer Science, MIS, or equivalent experience Familiarity with Extended Events and Query Store preferred Exposure to Azure SQL or hybrid cloud environments preferred T/SQL Development when needed for project preferred Experience with data engineering and building data pipelines (ETL/ELT) preferred Pay Rate and Benefits Salary commensurate with experience Group Insurance (Medical, Dental, Vision, Life, etc.). 401k with Employer Match. Discounted CarShield policies. Discounted Tuition at Lindenwood University. Professional development opportunities. Basketball, and other recreation available on-site. Fitness facilities, with the option to take classes led by on-staff personal trainer (at St. Peters headquarters). And more! PIe91767eaaf37-3538

Job Description Job Description Description This position is ideal for senior-level professionals to join the Finance Systems & Reporting team as a Sr. Finance Reporting Engineer. The Finance Engineer will be reporting to the Director, Global Finance Systems & Reporting based in San Jose, California (US) and would strategically engage with key members of finance function defining and delivering on the enterprise roadmap projects as well as own and help resolve day to day tactical problems and challenges. The Sr. Finance Reporting Engineer will be responsible for designing, developing, and maintaining enterprise financial reporting and analytics solutions. This role focuses on delivering accurate, scalable, and automated reporting capabilities by leveraging SAP technologies, cloud-based data platforms, and business intelligence tools to support strategic decision-making across the organization. Role expectations Lead the financial reporting life cycle end-to-end that includes conducting requirement gathering sessions with business, design the reporting solution, development, deployment, maintenance and training of the reporting solution to broader regional audience. Oversee the design and development for the planning system, OneStream, and be prepared to use other planning and reporting tools used at Align, including ERP, Consolidation Planning, and Business Intelligence software packages. Support financial close activities through data reconciliation, validation, and coordination of data loads for month-end, quarter-end, and year-end reporting. Responsible for designing, developing, and maintaining scalable data pipelines and integration workflows to ensure accurate and efficient data processing across systems. Monitor data flows, task chains, and job performance; implementing data quality controls and validation processes; troubleshooting and resolving data load issues; and optimizing data transformation and loading performance. Develop and troubleshoot a variety of Onestream components that include transformation rules, security models, custom dashboards, reports, business rules, and member formulas, with a focus on enhancing system functionality and efficiency. Lead the collaboration and development efforts for various financial Power BI dashboards required for finance, that will make analytics easier and reporting simplified for business at the same time maintaining data accuracy standards as required for financial reporting. Acting as a liaison between business and IT groups. Work with IT to help them understand business requirements and translate it in technical terminologies for them. Help business understand the technical solutions deployed and train them on how they can effectively use it for their needs. Identifying the gaps with existing solutions in place, finding out solutions to resolve them and work with IT/business to get them implemented. Lead the integration testing and user acceptance testing with business and IT collaboratively. Key Personnel responsible for financial close reporting of critical reports Key person responsible for ensuring financial data integrity and completeness for all finance data that will be needed for financial close reporting. Comply with data security and access control standards, maintains thorough process documentation, and provides production support, including participation in on-call rotations with the offshore team when required. Assist with special projects and ad-hoc requests, as necessary. What we're looking for Requires Bachelor's degree in CS, Information Technology, or a related field 12+ years of experience in Data loading and Monitoring systems to support the Finance organization. Strong understanding of financial reporting, FP&A, close processes, and management reporting. Hands-on experience with SAP Datasphere for data modeling, data warehousing, integration, and governance across SAP and non-SAP landscapes. Strong understanding of SAP RTR business processes, hands on experience working with FI-GL, COPA, AR/AP, Should be a self-starter who is able to work with minimal direction and exercises considerable latitude in determining objectives and approaches to assignments. Hands-on experience working with Onestream planning system or similar planning platforms such as Anaplan, Planful. Hands-on experience with SQL and object-oriented (VB.Net, C#) coding experience is preferred. The candidate will serve as a liaison between the finance user group, corporate report development team, and IT. Should be a team player and possess good interpersonal and communication skills, reflecting an ability to be patient and outgoing with people. Should be highly motivated, result focused, and act with a high sense of urgency. Should possess excellent planning and prioritization skills with the ability to multitask and maintain by adapting to change. Complementary skills Advanced Microsoft Outlook, Word, Excel and PowerPoint skills. Must have the ability to independently create spreadsheets and perform quantitative analysis. Prior experience working with Azure Datalake, S/4 HANA, SAP-ECC or SAP BW is a plus. Pay Transparency If provided, base salary or wage rate ranges are the range in which Align reasonably expects to set a candidate's pay for the posted position. Actual placement depends on the individual skills and experience level of a candidate plus the total compensation and equity across team members. For other locations outside of the primary location, the base salary range will be adjusted geographically. For Field Sales roles, the salary listed is the base pay only and does not include the applicable incentive compensation plan. A cost of living adjustment may be added to base pay for higher cost areas in the U.S. Our internship hourly rates are a standard pay determined based on the position and your location, year in school, degree, and experience. General Description of All Benefits We are pleased to provide a general description of the benefits Align offers to full-time employees in this position. Family Benefits. Align offers employees and their eligible dependents medical (with a Health Savings Account option for some plan offerings), dental, and vision in accordance with those plans. Align also offers to employees: Discounts on Invisalign and Vivera to employees and their eligible dependents after 90 days of employment Back-up Child/Elder Care and access to a caregiving concierge Family Forming Benefits - Available to Employees, and their spouse or domestic partner, covered under one of Align's health plans Breast Milk Delivery and Lactation Support Services Employee Assistance Program Hinge Health Virtual Physical Therapy - Available to all employees and eligible dependents (age 18+) enrolled in an Align medical Plan Employee benefits. Align offers its employees: Short-term and long-term disability insurance in accordance with those plans. Basic Life Insurance and Accidental Death and Dismemberment. Voluntary Supplemental Life Insurance for Employee, Spouse/Domestic Partner, and Child(ren) are available for purchase in accordance with those plans. Flexible Spending Accounts- Employees may be eligible to participate in a health care account (including a limited health FSA if enrolled in a HDHP), dependent care account, and a pre-tax commuter benefit plan. 401k plan (with a discretionary Company match of 50% up to 6% of eligible earnings up to a maximum match of 3%.). Employer match vests after two years - 25% year one and 100% at year two. Align offers traditional, Roth, and after-tax options. Employee Stock Purchase Program (Employees must work 20 hours or more and be employed on purchase date to be eligible). Paid vacation of up to 17 days during the first full year of employment (currently accrued at the rate of 5.24 hours each pay-period), which carries over to a maximum cap of 30 days. Annual paid vacation time accrual increases based on tenure. Both exempt and non-exempt employees who work 32 hours or more per week receive prorated vacation accrual based on their regularly scheduled work hours and tenure. Sick time is accrued throughout the year at the rate of one hour for every thirty worked. Employees can carry over unused sick leave each year, up to a maximum balance of 80 hours. 11 Company-designated paid holidays throughout the year. If employed for at least 12 consecutive months, Align will grant up to 6 weeks of paid Parental Leave. If employed for less than 12 consecutive months, Align will grant up to 4 weeks of paid Parental Leave. All parental leave must be completed within one year of the birth or placement of the child. Parental leave is in addition to any state and/or local parental leave benefits. Three days of paid bereavement leave. In some cases, due to travel the amount of paid leave may be extended to 5 paid days off. To the extent applicable state or local law offers more generous benefits, Align complies with any such law. Non-exempt employees will receive full pay for up to 10 days of jury duty. Exempt employees will receive their full salary during any week they serve and perform any work. Other insurance such as legal, critical illness, voluntary accident, long-term care, auto, home and pet insurance are available for purchase. To the extent applicable state or local law offers more generous benefits, Align complies with any such law.

Job Description Job Description Zilliz is a fast-growing startup developing the industry's leading vector database for enterprise-grade AI. Founded by the engineers behind Milvus, the world's most popular open-source vector database, the company builds next-generation database technologies to help organizations quickly create AI applications. On a mission to democratize AI, Zilliz is committed to simplifying data management for AI applications and making vector databases accessible to every organization. We're entering our next phase of 10x growth; more customers, larger datasets, and far higher expectations for reliability. You'll join a small, fast-moving Cloud Platform team that operates large-scale, multi-cloud, distributed database systems in production. This is a high-ownership role for engineers who want to move fast, build automation instead of toil, and take real responsibility for production stability. What you will do: Own the reliability, availability, and production stability of Zilliz Cloud as we scale through the next stage of growth Debug complex production issues across Kubernetes, cloud infrastructure, networking, storage, and distributed database systems Build automation and diagnostic tooling; log analysis, alert correlation, incident investigation, runbook automation, and remediation workflows so problems get solved once, not repeatedly Turn recurring incidents into reusable tools, automation, documentation, and product improvements Improve observability across latency, availability, throughput, and resource efficiency Partner with database and infrastructure engineers to make Zilliz Cloud more reliable, scalable, and automated What we are looking for: 3+ years building or operating production cloud systems, infrastructure platforms, database systems, or large-scale online services Bachelor's degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience Strong hands-on experience with Kubernetes, Docker, and at least one major cloud platform (AWS, GCP, or Azure) Solid understanding of distributed systems; availability, scalability, performance, failure recovery, and operational tradeoffs Experience with distributed databases, storage systems, search systems, or large-scale online systems is a strong plus Experience operating highly multi-tenant systems or large infrastructure fleets; thousands of nodes, clusters, tenants, or customer deployments is especially valuable Familiarity with modern cloud operations tooling such as Terraform, Helm, Argo CD, Prometheus, Grafana, and CI/CD systems Strong bias for action, and the drive to thrive in a fast-paced, rapidly scaling environment How we operate: High ownership: You own production reliability end-to-end. The whole system, not a slice of it. High autonomy, high trust, minimal process. Fast and focused: We ship often and keep a high bar. This team suits engineers who want velocity and a steep growth curve over red tape. Globally distributed: We work closely with our core engineering teams across APAC. Occasional early morning or evening syncs in exchange for an on-call setup designed around timezone coverage, not overnight pages. Zilliz is an Equal Opportunity Employer and welcomes people from all backgrounds, experiences, abilities, and perspectives. All qualified applicants will receive consideration for employment regardless of race, color, national origin, religion, sexual orientation, gender, gender identity, age, physical disability, or length of time spent unemployed. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job Description Job Description About SnapLogic SnapLogic is the Agentic Integration Company, integrating AI, data, applications, and microservices into one powerful platform that transforms how enterprises connect, automate, and scale. Unlike legacy integration tools, SnapLogic is built for the AI era and trusted by global leaders, including AstraZeneca, Adobe, Verizon, Epsilon and Sony. With its industry-leading platform, SnapLogic empowers every team across the enterprise to securely build faster, smarter, AI-connected workflows - all through natural language and intuitive low-code design. Join the Agentic Integration movement at The Role: We are looking for a Software Engineer to join our Agent Creator team, focusing on building and maintaining LLM integrations within the SnapLogic integration platform. In this role, you will design and implement AI-related Snap Packs that connect SnapLogic pipelines to diverse AI models, multimodal platforms, and evolving AI toolchains - enabling customers to build intelligent, enterprise-grade automation workflows at scale. You will own the full engineering lifecycle-from system design and prototyping through production deployment and operational excellence. Additionally, you will be a core driver of AI-assisted development practices within the team, combining your expertise with advanced AI coding agents to accelerate product delivery. What You'll Do: 1. Core Product & Integration Development AI Provider Integrations: Design, build, test, and ship Snap Packs for major AI providers, ensuring robust and high-performing connections. Cross-Provider Feature Parity: Implement and standardize advanced LLM capabilities across different providers, including Structured Outputs, Reasoning Models, Function Calling, Background Mode, and Vector Store integrations. Agent Framework & MCP: Develop and maintain the SnapLogic Agent Framework to support complex agentic workflows (incorporating iteration control, parallel tool calls, and observable execution via Agent Visualizer). Contribute to the Model Context Protocol (MCP) Server platform, including lifecycle management, observability, and registry. 2. Engineering Excellence & AI-Assisted Development AI-Augmented Coding: Leverage AI coding agents to write well-crafted, testable, and maintainable code, while maintaining full ownership, deep understanding, and accountability for the AI-generated codebase. Internal AI Innovation: Lead internal AI-driven initiatives to accelerate team velocity; rapidly prototype, validate, and productionalize internal AI tools (e.g., building dedicated AI Agents to automate Snap development). Code Quality & Operations: Write clean, structured, and testable Java/Python code adhering to checkstyle standards, maintaining a 90%+ unit test coverage target. Participate in code reviews and collaborate with QA/Release teams to validate builds across the production environment. 3. Strategy & Knowledge Sharing Trend Adoption: Stay at the forefront of the rapidly evolving AI ecosystem, selectively landing cutting-edge capabilities into the SnapLogic product line to deliver immediate customer value. Evangelism & Documentation: Institutionalize project learnings into high-quality technical documentation. Share knowledge through internal demos and evangelize engineering and AI best practices across the organization. What You'll Bring: Experience & Education: Bachelor's degree with a minimum of 2 years of related experience, or an advanced degree, or equivalent practical work experience. Agentic & AI Patterns: Strong foundational understanding of agentic design patterns (tool use, agent loops, function calling, structured outputs, reasoning models). Frameworks & APIs: Robust understanding of MCP (Model Context Protocol) or AI agent orchestration frameworks. Hands-on experience with LLM APIs (OpenAI, Azure OpenAI, Google Vertex AI, or Amazon Bedrock; Anthropic experience is highly preferred). Backend & Data Skills: Solid experience building or consuming REST APIs and a strong command of JSON Schema and structured data validation. Engineering Persona: Attention to Detail: Deep care for edge cases, comprehensive error handling, and intuitive user-facing validation/lint messages. Ambiguity Thriver: Ability to quickly self-learn, synthesize information, and drive towards a solution when facing ambiguous problems outside your immediate expertise. Collaboration: Strong cross-functional communication skills to work seamlessly across backend, platform, and UI teams. Nice to Have: Experience with SnapLogic or similar iPaaS (Integration Platform as a Service) / enterprise integration platforms. Familiarity with Maven-based build systems and modern CI/CD pipelines. Python experience (ideally for developing platform-layer components). The above range is the approximate annual U.S. base pay range for this position. Final offer amounts are determined by multiple factors, including candidate location, experience and expertise, and may vary from the range listed. In addition to base salaries, certain roles are also eligible for annual cash bonuses or commissions. All of our full time employees receive a comprehensive benefits package. Why Join: There's never been a better time to join our SnapSquad! At SnapLogic, we believe in empowering people - customers and employees alike - to integrate everything and create anything. From competitive salaries and equity packages to global wellness benefits, we're committed to your success and well-being. A Few Reasons You'll Love it Here: We're Innovators SnapLogic pioneered the first generative integration solution, SnapGPT, and continues to lead with a full suite of AI-powered tools - making integration faster, smarter, and accessible to more people. We're Recognized Leaders From being named a Visionary in multiple Gartner Magic Quadrants, leading the market in innovative AI reports from Aragon Research, or being recognized for AI in the Cloud Awards, we're setting the pace in a rapidly evolving market. We're Growing Fast Named one of Inc. 5000's Fastest Growing Private Companies in 2024, SnapLogic is scaling globally - and we want you to grow with us. We're Agentic Our platform empowers everyone across the enterprise to create automated, AI-connected workflows. That means more impact, less friction, and a bigger role for YOU in driving transformation. Are you ready to help the world integrate everything and create anything? Let's talk. Apply now and help shape the future of integration. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job Description Job Description Founded in 2012, H2O.ai is on a mission to democratize AI. As the world's leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose-built GenAI applications on their private data. With a focus on Sovereign AI-secure, compliant, and infrastructure-flexible deployments-H2O.ai delivers solutions that align with the highest standards of data privacy and control. Our open-source technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune 500. H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Chipotle, Workday, Progressive Insurance, and NIH. H2O.ai partners include NVIDIA, Dell Technologies, Deloitte, Ernst & Young (EY), Snowflake, AWS, Google Cloud Platform (GCP), VAST Data and MinIO. H2O.ai's AI for Good program supports nonprofit groups, foundations, and communities in advancing education, healthcare, and environmental conservation. With a vibrant community of 2 million data scientists worldwide, H2O.ai aims to co-create valuable AI applications for all users. H2O.ai has raised 256 million from investors, including Commonwealth Bank, NVIDIA, Goldman Sachs, Wells Fargo, Capital One, Nexus Ventures and New York Life. For more information, visit . About This Opportunity We are looking for a Principal AI Engineer who builds things that matter. You will design and ship end-to-end AI solutions for some of APAC's most complex enterprise problems - spanning agentic AI systems, LLM applications, and production ML pipelines. This is a hands-on engineering role embedded within a customer-facing field team, meaning your work will be seen, used, and evaluated by real enterprises from day one. You will work alongside Kaggle Grandmasters, ML engineers, and domain experts to deliver AI that goes beyond demos - into production, into workflows, and into measurable business outcomes. This position is based in San Francisco, Bay Area. What You Will Do Customer Engagement Leadership Lead end-to-end technical engagement with enterprise customers, acting as the senior point of accountability for delivery quality, stakeholder relationships, and outcomes. Manage multiple concurrent engagement streams simultaneously - coordinating workplans, resourcing, and milestones across cross-functional teams. Serve as the primary technical escalation point for customer issues, proactively identifying risks and driving resolution across engineering, product, and leadership. Build and maintain trusted relationships with customer data science teams, engineering leads, and executive stakeholders - translating business needs into technical direction and back again. Lead pre-sales and proof-of-concept engagements, setting the technical strategy and ensuring the team delivers demonstrations that build genuine enterprise trust. Represent H2O.ai externally at customer workshops, executive briefings, and technical deep-dives as a credible senior voice. Agentic AI & LLM Engineering Design and build agentic AI systems and multi-agent frameworks that automate complex, multi-step enterprise workflows. Develop and deploy LLM-powered applications using RAG, fine-tuning, prompt engineering, function calling, and tool use. Implement guardrails, evaluation frameworks, and responsible AI controls to ensure production-grade reliability and safety. Stay current with the rapidly evolving agentic AI landscape - MCP, LLM orchestration frameworks, reasoning models - and bring the best into customer engagements. End-to-End AI Application Development Own the full development lifecycle across multiple streams: from problem framing and data exploration through model development, API integration, and production deployment. Build scalable backend services and APIs that expose AI capabilities to enterprise applications and workflows. Integrate AI models into customer environments - cloud, on-prem, and hybrid - ensuring performance, stability, and maintainability at scale. Develop ML pipelines and LLMOps infrastructure that support continuous model improvement and monitoring in production. Team Collaboration & Delivery Excellence Coordinate delivery across engineers, program managers, and solution architects - ensuring workstreams are aligned, unblocked, and progressing to plan. Set the technical bar for the engagements you lead, reviewing outputs, shaping architecture decisions, and ensuring engineering quality across the team. Mentor and guide junior ML engineers and solution engineers within engagements, building team capability alongside delivery. Collaborate closely with H2O.ai product and engineering teams to surface customer feedback, shape roadmap input, and resolve platform-level issues. What We Are Looking For Experience & Background 8+ years of hands-on AI/ML engineering experience, including end-to-end model development and production deployment. Demonstrable experience leading technical delivery across complex, multi-stakeholder enterprise engagements - not just executing within them. Demonstrable experience building LLM-powered applications - RAG pipelines, agentic workflows, fine-tuned models, or similar. Strong Python engineering skills; experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and LLM tooling (LangChain, LlamaIndex, or equivalent). Experience deploying AI services in cloud or enterprise environments (AWS, Azure, GCP, on-prem Kubernetes). Skills & Capabilities Proven ability to manage multiple concurrent workstreams and coordinate cross-functional teams toward shared delivery milestones. Deep understanding of modern GenAI concepts: prompt engineering, RAG, fine-tuning, RLHF, model evaluation, guardrails, and LLMOps. Solid grounding in classical ML - able to select the right tool for the problem, not just default to the latest LLM. Backend development skills: REST APIs, containerisation (Docker/Kubernetes), and CI/CD pipelines for AI applications. Strong executive communication - able to run a board-level briefing one hour and a technical design review the next, credibly. Comfortable with ambiguity and able to set direction for a team when requirements are incomplete or evolving. How to Stand Out From the Crowd Kaggle or competitive ML experience. Familiarity with H2O.ai products, Wave, or H2O Document AI. Experience in financial services, healthcare, or other regulated industry AI deployments. Exposure to tabular foundation models, AutoML, or enterprise ML platforms. Prior experience in a customer-facing or field engineering role. Why H2O.ai? Market leader in total rewards Remote-friendly culture Flexible working environment Be part of a world-class team Career growth H2O.ai is committed to creating a diverse and inclusive culture. All qualified applicants will receive consideration for employment without regard to their race, ethnicity, religion, gender, sexual orientation, age, disability status or any other legally protected basis. H2O.ai is an innovative AI cloud platform company, leading the mission to democratize AI for everyone. Thousands of organizations from all over the world have used our cutting-edge technology across a variety of industries. We've made it easy for people at all levels to generate breakthrough solutions to complex business problems and advance the discovery of new ideas and revenue streams. We push the boundaries of what is possible with artificial intelligence. H2O.ai employs the world's top Kaggle Grandmasters, the community of best-in-the-world machine learning practitioners and data scientists. A strong AI for Good ethos and responsible AI drive the company's purpose. Please visit to learn more. Powered by JazzHR ZnRHQBiPpf

Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating responsible and reliable AI-powered systems. 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 exceptional products for our customers. In Risk Tech, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our customers, our business, or our communities. In this role at Risk Tech, you will work with our GRC team and partners across the company to build and deploy proprietary solutions for Risk management that are powered by state-of-the-art AI technology. Our products, enhanced with the transformative power of AI, are central to our business and deliver tremendous customer value. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Partner with a cross-functional team of engineers, data scientists, product managers, and designers to deliver AI-powered products that change how our associates work and provide value to our customers. Design, develop, test, deploy, and support AI software components utilizing machine learning models, including model evaluation and experimentation, large language model inference, similarity search, guardrails, governance, observability and agentic AI. Fine-tune, develop and evaluate machine learning and foundation models, Collaborate as part of a cross-functional Agile team to create and enhance software that utilizes state-of-the-art AI and ML capabilities Contribute thought leadership and technical vision to the long term roadmap of pioneering AI systems at Capital One. Leverage a broad stack of Open Source and SaaS AI technologies. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues. Retrain, maintain, and monitor models in production. Construct optimized data pipelines to feed ML models. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. 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. You are a passionate communicator, comfortable with explaining complex technical concepts to non-technical partners across the business, sometimes in front of large audiences. 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 enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Passion for staying abreast of the latest AI research and AI systems, and judiciously applying novel techniques in production Strategic & Business-Oriented: You think beyond the technology, deeply understanding business needs and how AI can solve them. You don't just build; you strategize and prioritize work that delivers the greatest business value. Highly Collaborative & Transparent: You are a natural partner, working seamlessly across engineering, product, and data science teams. You communicate your progress, blockers, and decisions clearly and proactively, ensuring everyone is aligned. You love sharing knowledge and insights and are committed to the success of the entire team. Technically Mature & Humble: You possess a strong foundation in engineering and mathematics. You are a resilient problem-solver who can bring clarity to complex, undefined problems and articulate your findings concisely. You demonstrate professional maturity by committing to and executing on team decisions. Flexible & Fungible: You are eager to roll up your sleeves and contribute wherever the team needs you most. You are comfortable working across different aspects of the tech stack and adapting to evolving priorities. A Lifelong Learner: You love staying current with the latest AI research and can apply novel techniques to production systems judiciously, always with a focus on business impact. Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 7+ years of experience designing, developing, delivering, and supporting AI services at scale 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing AI and ML algorithms or technologies using Python 2+ years of experience with Retrieval Augmented Generation (RAG) 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). 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 Lead Machine Learning Engineer McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer Richmond, VA: $179,400 - $204,700 for Lead Machine Learning 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 . click apply for full job details

Job Description Job Description About The Role We are seeking an experienced Site Reliability Engineer (SRE) with a strong focus on DevSecOps to join our growing engineering team. In this role, you will oversee and maintain the reliability, security posture, and operational hygiene of our cloud infrastructure, APIs, and software supply chain. You will drive patch management programs, harden our Cloud infrastructure, and maintain our code repositories to ensure all systems remain compliant, secure, and scalable. This role is ideal for an engineer who thrives at the intersection of operations and security, is passionate about automation, and takes pride in keeping complex environments clean, auditable, and resilient. Key Responsibilities Own and execute end-to-end patch management across AWS compute resources (EC2, ECS, Lambda runtimes, EKS nodes), third-party dependencies, and OS-level packages. Monitor, triage, and remediate vulnerabilities identified by security scanning tools (e.g., AWS Inspector, Dependabot, Security Hub, or equivalent), prioritizing by CVSS severity and business impact. Maintain and enforce branch protection rules, secret scanning policies, and dependency update workflows across all code repositories. Design and implement automated pipelines for continuous compliance checking, security testing (SAST/DAST/SCA), and infrastructure drift detection. Collaborate with IT & Info-Sec SMEs on AWS IAM roles and policies, VPC configurations, Security Groups, CloudTrail, Config, and GuardDuty to ensure least-privilege access and auditability. Collaborate with development teams to embed security controls into CI/CD pipelines (GitHub Actions, CodePipeline, or equivalent) without impeding developer velocity. Support the reliability and availability of production APIs - including uptime monitoring, incident response, runbook creation, and post-incident reviews. Partner with Legal and Data Governance SMEs on API access procedures and monitoring. Define and track SLOs/SLAs for internal and external APIs; implement alerting and dashboards using observability tooling (e.g., CloudWatch, Datadog, Grafana). Lead periodic infrastructure and dependency audits; produce clear reports on patch compliance status and open risk items for engineering and security leadership. Maintain thorough documentation of patching schedules, runbooks, access policies, and environment configurations. Participate in on-call rotation and contribute to a culture of continuous improvement. Required Qualifications Bachelor's Degree in Computer Science, Information Systems, or a related field (or equivalent practical experience). 5+ years of professional experience in a Site Reliability Engineering, Software Engineering, DevOps, or DevSecOps role. Demonstrated expertise managing AWS environments - including EC2, Lambda, ECS/EKS, S3, RDS, IAM, VPC, CloudTrail, Config, and GuardDuty. Experience with various cloud environments: AWS, Azure, GPC Strong experience with GitHub administration: branch protection, Actions workflows, secret scanning, Dependabot, and code owners. Hands-on experience with patch management and vulnerability remediation at scale, including OS-level patching (Amazon Linux, Ubuntu) and dependency lifecycle management. Proficiency with infrastructure-as-code tools (Terraform, CloudFormation, or AWS CDK). Experience integrating security tooling (SAST, DAST, SCA, container scanning) into CI/CD pipelines. Solid understanding of API reliability patterns: health checks, rate limiting, circuit breakers, and observability. Familiarity with compliance frameworks relevant to cloud environments (SOC 2, CIS Benchmarks, NIST CSF). Strong scripting skills in Python, Bash, or similar for automation and tooling. Excellent communication skills and ability to translate technical risk for non-technical stakeholders. Build observation (logging, metrics, alerting) systems to make sure system works well, and develop response plans. Preferred Qualifications AWS certifications (e.g., AWS Certified Security - Specialty, AWS Certified DevOps Engineer - Professional). Experience with container security and Kubernetes (EKS) hardening. Familiarity with CSPM tools (e.g., Wiz, Prisma Cloud, AWS Security Hub) for continuous cloud posture management. Experience managing API gateways (AWS API Gateway, Kong, or similar) including security policy enforcement. Exposure to secrets management solutions (AWS Secrets Manager, HashiCorp Vault). Knowledge of SBOM (Software Bill of Materials) generation and management. Experience with incident response playbooks and tabletop exercises. Familiarity with Agile/Scrum methodologies and cross-functional engineering teams. Compensation The anticipated base salary range for this position is $150,000 annually, plus eligibility for a 15% annual performance bonus. Actual compensation will be determined based on several factors, including skills, experience, education, certifications, and geographic location. In addition to base salary and bonus eligibility, we offer a competitive benefits package, including medical, dental, vision, 401(k), paid time off, and other employee benefits.

Job Description Job Description At Sonatus, we're driving the transformation to AI-enabled software-defined vehicles. Traditional automotive software methods can't keep pace with consumer expectations shaped by the mobile industry-where features evolve rapidly, update seamlessly, and improve continuously. That's why leading OEMs trust Sonatus to accelerate this shift. Our technology is already in production across more than 8 million vehicles on the road today and rapidly expanding. Headquartered in Sunnyvale, CA, with 250+ employees worldwide, Sonatus combines the agility of a fast-growing company with the scale and impact of an established partner. Backed by strong funding and proven by global deployment, we're solving some of the most interesting and complex challenges in the industry. Join us and help redefine what's possible as we shape the future of mobility. Role Summary: We are seeking a Senior Staff AI Engineer with a combination of architectural expertise and production rigor to lead the development of an Agentic Framework to support our AI applications. In this role, you will be the technical anchor for our AI offerings, working to deliver a production-grade Agentic Operating Layer for software-defined vehicles. This is a 50% Architecture / 50% Implementation position. You will be responsible for designing and implementing an extensible architecture that bridges high-velocity vehicle telemetry with sophisticated AI reasoning. We need a leader who is collaborative by nature but decisive in execution-someone who can drive architectural consensus and take full accountability for the performance, safety, and scalability of the resulting system. Responsibilities: Lead the architecture and design of an extensible AI platform. Drive architectural consensus across teams on AI-core decisions to ensure platform unification. Lead the development of agentic orchestration by designing and implementing mission-critical components that allow AI agents to decompose complex goals into actionable sub-tasks. Design and implement a versioned prompt registry allowing for model-agnostic routing and A/B testing of system prompts Engineer the privacy shield for PII redaction and the hallucination verifier to audit AI-generated actions before execution Conduct the full cycle of data modeling and algorithm development, including modeling, training, tuning, validating, deploying, and maintaining services (AI breadth). Strong domain expertise in the AI area, including LLM, RAG, fine-tune large models, traditional ML models, etc. (AI depth) Stay current with industry trends and advancements in data science and AI technologies. (State-of-the-Art) Perform data analysis and offer insights to inform business decisions across multiple domains. Adhere to data privacy and security protocols to uphold the confidentiality of sensitive information. Document and communicate technical designs, processes, and best practices to stakeholders using visualizations and presentations. Take charge of projects, ensuring timely completion in a dynamic work environment. Qualifications: Master's or PhD in Computer Science, Engineering, Mathematics, Applied Sciences, or a related field preferred. Bachelor's degree required. 10+ years of software engineering experience with 4+ years dedicated to shipping production-scale AI/Agentic systems. You have a track record of moving projects from whiteboards to global cloud deployments. Strong programming skills in languages such as Python, Java, or C++, with hands-on experience in relevant frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Expert-level experience with stateful orchestration frameworks (e.g., LangGraph, AutoGen, or similar). You understand the nuances of managing state across complex, multi-step AI missions. Strong experience grounding AI in structured/unstructured Big Data environments. Practical knowledge of traditional databases, streaming analytics, and Vector databases. Proven experience building multi-agent systems and frameworks with adaptive orchestration Deep understanding of Jailbreak Detection (e.g., LlamaGuard) and PII masking techniques to ensure safe LLM interactions in regulated environments In-depth knowledge and understanding of current machine learning algorithms, AI technologies, and platforms. Solid experience in data preprocessing, feature engineering, and model evaluation techniques. Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes) is a plus. Strong knowledge of software development best practices, version control systems, and agile methodologies. Results-driven with a positive can-do attitude and excellent problem-solving skills. Exceptional verbal and written communication skills, with the ability to collaborate effectively with cross-functional teams. Experience in the automotive industry is highly desirable. Experience building multi-tenant "Platform-as-a-Service" (PaaS) models is desirable. Benefits Offered: Competitive compensation and equity program Health care plan (Medical, Dental & Vision) Flexible and Dependent Care Expense program Retirement plan (401k) Life Insurance (Basic, Voluntary & AD&D) Unlimited paid time off per year, 15 paid holidays Hybrid office work arrangement/flexibility Perk Offerings include: Complimentary lunches, snacks, and beverages during on-site working days Wellness benefit allowances (towards gym membership and fitness programs) Internet reimbursement Computer Accessory Allowance Employee Engagement Offerings: Departmental team building and outings Employee Referral Program Culture/Employee Satisfaction Surveys - Feedback matters! The posted salary range is a general guideline and represents a good faith estimate of what Sonatus ("Company") could reasonably expect to pay for a base salary for this position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, geographic location and external market pay for comparable jobs. The Company reserves the right to modify this range in the future, as needed, as market conditions change. Base Salary Pay Range $227,500-$300,000 USD

Job Description Job Description Job Description Senior Engineer, Internal Tools, Artificial Intelligence (AI) Required, Work From Home The Senior AI Engineer is the engineering backbone of the internal tools team. Building and maintaining the platforms that every team in the company relies on. Your work directly increases organizational efficiency and enables teams to move faster. The Senior AI Engineer will own systems end-to-end, from scoping and architecture through production deployment and iteration, connecting multiple business systems into a seamless, reliable internal ecosystem. This position is 100% Remote. Senior Engineer Responsibilities: Build & Ship: - Design, build, and maintain internal platforms and tools that serve People, Finance, Ops, Sales, and Engineering teams. - Own features, end-to-end requirements, architecture, implementation, testing, deployment, and monitoring. - Write clean, well-tested, production-grade code. You hold yourself to the same bar as customer-facing products. Architecture & Integration: - Build API-first integrations across the internal ecosystem connecting HRIS, CRM, finance platforms, knowledge management, and developer tools into a coherent stack. - Design for reliability, performance, and scale what you build today must hold as the company grows 5-10x. - Eliminate data silos. Build clean data pipelines that maintain a single source of truth across systems. - Own your services in production: monitoring, alerting, incident response, and post-mortems. AI & Automation: - Build AI/LLM-powered features into internal workflows, automating approvals, knowledge retrieval, reporting, content generation, and operational processes. - Move fast from prototype to production. You know the difference between a demo and a system that works at scale. - Stay current on emerging AI capabilities and proactively identify where they unlock step-change improvements in internal productivity. Collaboration & Influence: - Work directly with business stakeholders to understand pain points and translate them into technical solutions. You don't wait for a spec you help shape it. - Pair with and mentor junior engineers. Raise the technical bar through code reviews, design reviews, and leading by example. - Influence technical direction: propose architectural improvements, challenge assumptions, and drive best practices across the team. Qualifications Senior Engineer Qualifications: - 5+ years of professional software engineering experience, with meaningful time spent building internal tools, platforms, or business systems. - Artificial Intelligence (AI) experience required. - Strong full-stack or backend engineering skills. Proficient in at least one of: Python, Go, TypeScript/Node.js, or Java. - Solid understanding of Cloud Infrastructure (GCP/AWS/Azure), Containerization (Docker/Kubernetes), CI/CD Pipelines, and modern DevOps practices. - Hands-on experience building and maintaining API integrations between third-party SaaS platforms (e.g., Workday, Salesforce, Slack, NetSuite). - Strong data fundamentals: relational databases, data modelling, ETL/ELT pipelines, and working knowledge of SQL. - Comfort with ambiguity. You can take a vague business problem, break it down, and deliver a working solution without heavy handholding. - Clear communicator who can explain technical tradeoffs to non-technical stakeholders. - Experience with workflow orchestration tools (Temporal, Airflow, Prefect) or integration platforms (Workato, Tray.io, MuleSoft) is a plus. - Frontend experience with React, Next.js, or equivalent modern frameworks is a plus. - Familiarity with HRIS, ERP, or people systems data models and processes is a plus. - Experience at a high-growth or AI-native company is a plus. - Contributions to developer experience tooling, CLIs, or internal SDKs is a plus. - Experience building or integrating AI/LLM-powered features not just experimenting, but shipping to real users is a plus. Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc. Looking to hire a Senior Engineer in San Francisco, CA or in other cities? Our IT recruiting agencies and staffing companies can help. We help companies that are looking to hire Senior Engineers for jobs in San Francisco, California and in other cities too. Please contact our IT recruiting agencies and IT staffing companies today! Additional Information Please check out all of our jobs at .

Job Description Job Description Who We Are & Why Join Us Avathon is the leading Industrial AI autonomy platform, helping customers across heavy industries energy, mining, manufacturing, aerospace, defense, and logistics accelerate the journey toward autonomous operations. Our platform is built on a Computational Knowledge Graph foundation that contextualizes and connects operational data across siloed systems, bringing together time series, structured, unstructured, and machine vision data to power AI-driven applications in asset performance management, supply chain intelligence, visual AI, and global trade management. With capabilities spanning digital twins, normal behavior modeling, natural language processing, and computer vision, Avathon delivers real-time predictive intelligence and agentic decision-making at industrial scale. Cutting-Edge AI Innovation Join a team at the forefront of AI, developing groundbreaking solutions that shape the future. High-Growth Environment Thrive in a fast-scaling startup where agility, collaboration, and rapid professional growth are the norm. Meaningful Impact Work on AI-driven projects that drive real change across industries and improve lives. Learn more at: About the Role As a Senior AI Engineer at Avathon, you will play a key role in designing and delivering advanced AI solutions with a strong emphasis on Generative AI and Large Language Models (LLMs). You will apply scientific rigor to develop scalable, production-ready machine learning systems that drive measurable business impact, working on challenging problems in forecasting, demand planning, renewable energy optimization, anomaly detection, and prescriptive maintenance. With minimum 5 years of industry experience, you are expected to bring strong expertise in statistical modeling, ML engineering, and modern AI architectures, particularly in GenAI and LLM-based applications. This role offers the opportunity to work on high-impact projects that shape next-generation AI capabilities within the organization. You Will Design, develop, and deploy machine learning and Generative AI solutions to solve complex business problems Build, fine-tune, and optimize Large Language Models (LLMs) and transformer-based architectures for real-world applications Apply rigorous scientific methodologies to experimentation, model evaluation, and performance optimization Develop scalable ML pipelines and production-grade systems in collaboration with Engineering teams Conduct prompt engineering, model alignment, evaluation, and performance benchmarking for GenAI applications Work closely with Product, Engineering, and Business stakeholders to translate ambiguous requirements into data-driven AI solutions Instrument and monitor LLM applications in production using observability tools, tracking cost, latency, quality, and drift Contribute to model governance, responsible AI practices, and performance monitoring in production environments Stay current with advancements in Generative AI, LLM research, and applied machine learning, incorporating relevant innovations into company solutions You'll Have Master's or PhD in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field Minimum 5 years of hands-on industry experience in AI engineering, machine learning, data science, or applied AI roles Strong experience with Generative AI frameworks and Large Language Models (e.g., transformer architectures, fine-tuning, RAG systems) Proficiency in Python and modern ML/AI libraries such as PyTorch, TensorFlow, Hugging Face, or equivalent ecosystems Solid understanding of statistical modeling, experimentation, and model evaluation methodologies Experience building and deploying ML models into production environments Familiarity with data engineering workflows and cloud-based ML platforms (AWS, GCP, or Azure) Strong problem-solving skills with the ability to work independently on complex and ambiguous problem statements Excellent communication skills with the ability to present technical insights clearly to cross-functional stakeholders Preferred Qualifications Experience implementing Retrieval-Augmented Generation (RAG), vector databases, and embedding-based search systems Hands-on experience with LLM observability platforms (e.g., Langfuse, LangSmith, Arize Phoenix, Weights & Biases) for tracing, cost tracking, and quality monitoring in production Experience with LLM evaluation frameworks (e.g., RAGAS, DeepEval) and evaluation patterns such as LLM-as-judge and automated regression testing Practical experience deploying LLM applications with guardrails, prompt versioning, hallucination detection, and model drift monitoring Exposure to distributed training, model optimization, and scalable inference architectures Knowledge of MLOps practices, CI/CD for ML (Travis CI, Jenkins), and model lifecycle management Prior experience applying AI solutions in industrial or asset-intensive environments Experience working in fast-paced startup or product-driven environments Industry experience in one or more of the following domains: Mining, Oil & Gas, Aerospace, Supply Chain, Logistics, or Renewable Energy Benefits & Perks What are the benefits and perks at Avathon? Below are some highlights we offer to our U.S. full-time employees we'd love to connect and share more! Evolving culture with the opportunity to drive new ideas and technology Stock Option Grants Medical Coverage and Parental Leave Plans 401k with Employer Match Monthly Technology Allowance Newly renovated office space located near Pleasanton, CA including fully stocked beverage and snack areas Contract and temporary roles are not eligible for the above benefits. Compensation Pay Range: $130k - $155k salary annually. Pay for this position is based on a number of factors including geographic location and may vary depending on job-related knowledge, skills, and experience. Location: This role is not remote. Candidates must be based in the Bay Area, CA and are expected to report to our Pleasanton office 5 days a week. Avathon is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, pregnancy, genetic information, disability, status as a protected veteran, or any other protected category under applicable federal, state, and local laws. Avathon is committed to providing reasonable accommodations throughout the recruiting process. If you need a reasonable accommodation, please contact us to discuss how we can assist you.

Job Description Job Description Company Description At PayNearMe, we're on a mission to make paying and getting paid as simple as possible. We build innovative technology that transforms the way businesses and their customers experience payments. Our industry-leading platform, PayXM , is the first of its kind-designed to manage the entire payment experience from start to finish. Every click, swipe or tap is seamless, fast and secure, helping non-commerce businesses boost customer satisfaction, accelerate payments, and reduce costs. Our single platform handles it all: cards, ACH, digital wallets such as PayPal, Venmo, Cash App Pay, Apple Pay and Google Pay, and even cash at more than 62,000 retail locations nationwide. Today, thousands of businesses across consumer lending, iGaming and online sports betting, property management, and tolling trust PayNearMe to deliver a payment experience that drives real results. In September 2025, we raised a $50 million Series E funding round to accelerate our growth. We're a team of 300+ employees across 41 states, headquartered in Silicon Valley with satellite offices in Dallas, TX and Holmdel, NJ. Join us and be part of a team that's shaping the future of payments-one experience at a time. As our Site Reliability Engineer, you will design, build, and maintain the systems and infrastructure that power our applications, ensuring their reliability, scalability, and performance. You will bring a software engineering approach to operations, automating processes, and continuously improving the infrastructure and tools to support our business needs. Responsibilities Infrastructure Management: Design, implement, and maintain scalable and resilient infrastructure using Terraform for infrastructure as code, ensuring high availability and performance Kubernetes and Containers: Deploy, manage, and optimize Kubernetes clusters and containerized applications using Docker. Implement best practices for container orchestration and management Systems and Application Monitoring/Observability: Develop and maintain comprehensive monitoring and observability solutions using Datadog. Ensure detailed visibility into system performance and application health SLOs and SLA Management: Define, monitor, and maintain Service Level Objectives (SLOs) and Service Level Agreements (SLAs) to ensure reliable and consistent service delivery Incident Response and Troubleshooting: Respond to incidents, perform root cause analysis, and implement solutions to prevent recurrence. Participate in post-incident reviews and contribute to blameless postmortems Reliability and Production Environment Management: Ensure the reliability and stability of our production environments. Continuously assess and improve system reliability, identifying and addressing potential points of failure Automation and Scripting: Develop automation scripts and tools to reduce manual intervention and improve system reliability using Python, Bash, or Go. Implement and improve CI/CD pipelines CI/CD Pipeline Management: Enhance and maintain continuous integration and continuous deployment pipelines using GitLab CI. Ensure seamless and reliable deployment processes Capacity Planning and Scaling: Assist in capacity planning and ensure that systems are scalable to meet future demands. Implement auto-scaling strategies where applicable Security and Compliance: Implement security best practices and ensure compliance with industry standards. Regularly review and update security policies and procedures Collaboration and Support: Work closely with development teams to ensure reliability and scalability of new features and services. Provide technical support and guidance on infrastructure-related issues Software Engineering for Operations: Develop and maintain internal tools and services that enhance the efficiency and reliability of our operations On-Call Rotation: Participate in an on-call rotation to address production issues and collaborate in incident response efforts Qualifications +3 years of experience in SRE, DevOps, or a related role Cloud Platform Experience: Proficient with cloud platforms such as AWS, GCP, or Azure Experience with EC2, RDS, VPCs, and security groups is essential. Kubernetes and Containers: Strong experience with Kubernetes and Docker, including deployment, scaling, and management of containerized applications Infrastructure as Code: Expert in using Terraform for infrastructure as code. Proficient with configuration management tools such as Ansible, Puppet, or Chef Monitoring and Observability: Extensive experience with monitoring and observability tools like Datadog, Prometheus, Grafana, ELK stack, or Splunk. Skilled in setting up detailed monitoring and logging systems SLOs and SLA Management: Proven ability to define, monitor, and maintain SLOs and SLAs to ensure reliable service delivery Scripting and Automation: Strong skills in scripting languages like Python, Bash, or Go. Experience automating repetitive tasks and processes CI/CD Practices: Familiarity with GitLab CI or similar tool for continuous integration and deployment. Experience in setting up and managing pipelines Production Environments: Experience supporting production environments running Go or Ruby/Rails applications Tool Development: Ability to write and update tools to support infrastructure and application management, demonstrating the principle that "SRE is what happens when you ask a software engineer to design an operations team DevOps Best Practices: Deep understanding of DevOps principles, practices, and tools to drive continuous improvement in the software development lifecycle Soft Skills: Strong organizational skills, attention to detail, and the ability to work collaboratively in a team environment. Excellent documentation skills to ensure accurate and detailed records Problem-Solving Ability: Excellent analytical and problem-solving skills to diagnose and resolve complex system issues quickly and effectively The annual base salary range for this role represents PayNearMe's good-faith estimate of the base salary it reasonably expects to offer for this position at the time of hire. Actual compensation may vary based on factors including the candidate's experience, qualifications, skills, and work location. PayNearMe may offer compensation outside of this range in certain circumstances. This position will remain posted until filled. Annual Salary Range $180,000-$200,000 USD Why Join Us?: Competitive salary and benefits with growth-company options grant Fast- paced and professional work culture Stock options with standard startup vesting - 1 year cliff; 4 years total $50 monthly communication expense stipend to go towards your phone/internet bill $250 stipend to enhance your WFH setup Reimbursement for peripheral equipment: monitor (up to $400), keyboard and mouse (up to $200) Premium medical benefits including vision and dental (100% coverage for employees) Company-sponsored life and disability insurance Paid parental bonding leave Paid sick leave, jury duty, bereavement 401k plan Flexible Time Off (our team members typically take off 3-4 weeks per year) Volunteer Time Off 13 scheduled holidays PayNearMe strives to create a workplace where all employees thrive. Our core values represent who we are today and we take pride in the way we work with each other as well as with our stakeholders. We're in this together to do the right thing. We deliver real results we are proud of while remaining respectful, transparent, and flexible. PayNearMe is an equal opportunity employer. We are diligently and thoughtfully working towards cultivating a diverse workforce which in turn, enhances our products and services for the communities we serve. Applicants who represent all backgrounds are strongly encouraged to apply. CALIFORNIA CONSUMER PRIVACY ACT: APPLICANT NOTICE Effective Date: January 1, 2020 Last Reviewed on: December 23, 2019 PayNearMe, Inc. (the "Company") is providing you with this Notice ("Notice") to inform you about: the categories of Personal Information that the Company collects and maintains about applicants; and the purposes for which the Company uses that Personal Information. For purposes of this Notice, "Personal Information" means information that identifies, relates to, describes, is capable of being associated with, or could reasonably be linked, directly or indirectly with, a natural person that the Company may collect in connection with screening applicants for job openings at the Company. Identifiers and Professional or Employment-Related Information. The Company collects identifiers and professional or employment-related information, which may include some or all the following: real name, nickname or alias, postal address, telephone number, e-mail address, membership in professional organizations, professional certifications, language skills, and current and past employment history. The Company collects this Personal Information to evaluate previous job performance and consider applicants for positions, to develop a talent pool and plan for succession . click apply for full job details

Senior Machine Learning Engineer (AI Foundations) As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. Capital One is accelerating the adoption of state of the art AI research to create simpler, safer banking experiences for over 100 million customers. The AI Foundations team spearheads this mission by developing advanced LLMs and autonomous agentic systems capable of complex reasoning and real world problem solving. Their comprehensive research framework prioritizes foundational model architecture, operational efficiency, and responsible AI practices to ensure all systems are trustworthy and scalable. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply) At least 3 years of experience designing and building data-intensive solutions using distributed computing At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) At least 1 year of experience productionizing, monitoring, and maintaining models Preferred Qualifications: 1+ years of experience building, scaling, and optimizing ML systems 1+ years of experience with data gathering and preparation for ML models 2+ years of experience developing performant, resilient, and maintainable code Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience with distributed file systems or multi-node database paradigms Contributed to open source ML software Authored/co-authored a paper on a ML technique, model, or proof of concept 3+ years of experience building production-ready data pipelines that feed ML models Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). 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: $161,800 - $184,600 for Senior Machine Learning Engineer New York, NY: $176,500 - $201,400 for Senior Machine Learning 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. 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).

Sr. Lead, Machine Learning Engineer (Enterprise Platforms Technology) As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. Enterprise Platforms Technology (EPTech) comprises many of Capital One's most important enterprise platforms. We play an essential role in establishing practices for building technology solutions across the company, while also delivering capabilities that exemplify those practices. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's degree At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 3 years of experience building, scaling, and optimizing ML systems At least 2 years of experience leading teams developing ML solutions Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models 3+ years of people management experience ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents 3+ years of experience building production-ready data pipelines that feed ML models Ability to communicate complex technical concepts clearly to a variety of audiences 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: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer New York, NY: $250,800 - $286,200 for Sr. Lead Machine Learning 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. 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).

Senior Lead AI Engineer (MLXT) Overview: 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. As a Senior Lead AI Engineer, you will drive critical technical initiatives that shape the future of enterprise AIML infrastructure targeted to transform the business analysis experience in a highly regulated environment. You will play a pivotal role in modernizing our core Analyst & AIML workflow orchestration layer and user interface, integrating frontier generative AI capabilities and self-serve tooling to enable no-code/low-code, well-governed model development for business domain experts. In this role, you will: Modernize Workflows: Advance the orchestration layer and UI with generative AI capabilities and self-serve tooling to democratize AI development through governed, low-code/no-code tools for business domain experts. Build Agentic-Driven Infrastructure: Modernize our platform services with agentic infrastructure that is reliable, scalable, secure, and seamlessly adheres to enterprise guardrails. Drive AutoML Innovation: Scale enterprise-grade managed AutoML offerings for tabular and time-series data to radically reduce solution time-to-market from weeks to days. Engineer AI-Driven Controls: Evolve the core component marketplace by engineering cutting-edge, automated governance frameworks 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 enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer 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 6 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 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 7 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, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, 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 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 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: $229,900 - $262,400 for Sr. Lead AI Engineer McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Lead AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Lead 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. 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).

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). 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. New York, NY: $215,200 - $245,600 for Lead Machine Learning 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. 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).