239 jobs found

Own Every Moment at NetApp At NetApp, your ideas power innovation. We lead in intelligent data infrastructure-delivering unified storage, integrated data services, and solutions that help organizations unlock the full potential of their data, from AI to multicloud. Ready to innovate and contribute to our path to $10B? Here, you'll collaborate with passionate teams, tackle real-world challenges, and see your impact in how customers transform and grow. If you're ready to bring curiosity, creativity, and drive to every moment, NetApp is where your journey begins. Job Summary NetApp is hiring a principal-level product leader to own the AI product strategy for Azure NetApp Files (ANF)-a first-party, fully managed enterprise file service on Microsoft Azure, delivered in deep partnership between NetApp and Microsoft. In the spirit of NetApp's "business builder" cloud roles, you will translate a fast-moving AI landscape into differentiated platform capabilities, joint roadmap bets with Microsoft, and enterprise outcomes (performance, data locality, governance, and time-to-value for AI pipelines). You will sit at the intersection of enterprise storage, Azure AI infrastructure, and industry AI workloads, ensuring ANF is positioned and built as a strategic data foundation for training, inference, RAG, analytics, simulation, and agentic workflows-without forcing customers to abandon enterprise file semantics, protection, or hybrid operating models. Role Overview We need a highly strategic and deeply technical principal PM who can: Define multi-year AI vision and roadmap for ANF in the context of Azure AI services, GPU estates, data platforms, and regulated enterprise environments. Turn emerging patterns (LLMs, RAG, agents, orchestration, multimodal data, vector retrieval, high-throughput checkpointing) into concrete product requirements and joint go-to-market narratives with Microsoft. Balance hyperscaler co-development constraints with NetApp differentiation (enterprise data services, multiprotocol access, lifecycle management, resiliency, and cross-cloud consistency where relevant). Responsibilities AI strategy & roadmap Own end-to-end AI strategy for ANF: problem selection, success metrics, phased delivery, and competitive positioning vs. other Azure and AI-native storage options. Prioritize investments across performance, scale, data services, protocol and API surfaces, and operational excellence for AI pipelines. Workload-led product definition Drive requirements for AI-centric scenarios, including: Training and inference data planes (high throughput, low latency, checkpointing, bursty I/O) RAG and enterprise search (datasets, versioning, clones, refresh patterns) Agentic workflows and orchestration (durable shared state, tool/data access patterns-where productized responsibly) Large multimodal and enterprise datasets (governance, access control, lifecycle) Analytics and simulation adjacencies (HPC/EDA-style throughput, shared filesystem semantics) Hyperscaler & ecosystem partnership Partner with Microsoft teams across Azure AI / Foundry, Azure Machine Learning, AKS / container platforms, GPU infrastructure, data/analytics (e.g. Databricks-style patterns on Azure), and core Azure storage/networking dependencies. Align ANF's AI story with Azure-wide AI data guidance and reference architectures, and feed real customer workload evidence back into joint planning. Cross-functional leadership Lead across engineering, product marketing, sales, customer success, and professional services to ship capabilities and repeatable reference architectures / proof points. Engage strategic customers and design partners to validate pain, quantify value, and de-risk roadmap bets. Market intelligence & evangelism Monitor AI infrastructure trends (models, frameworks, orchestration, data formats) and competitor moves; translate into differentiated bets. Represent ANF as a credible technical executive in briefings, advisory councils, and industry forums. Industry segmentation Tailor AI storage strategy for segments where file semantics and performance matter, for example: semiconductor/EDA, manufacturing, healthcare imaging, financial services, energy, media & entertainment, and HPC/simulation-including compliance and data residency realities. AI strategy & roadmap Own end-to-end AI strategy for ANF: problem selection, success metrics, phased delivery, and competitive positioning vs. other Azure and AI-native storage options. Prioritize investments across performance, scale, data services, protocol and API surfaces, and operational excellence for AI pipelines. Workload-led product definition Drive requirements for AI-centric scenarios, including: Training and inference data planes (high throughput, low latency, checkpointing, bursty I/O) RAG and enterprise search (datasets, versioning, clones, refresh patterns) Agentic workflows and orchestration (durable shared state, tool/data access patterns-where productized responsibly) Large multimodal and enterprise datasets (governance, access control, lifecycle) Analytics and simulation adjacencies (HPC/EDA-style throughput, shared filesystem semantics) Hyperscaler & ecosystem partnership Partner with Microsoft teams across Azure AI / Foundry, Azure Machine Learning, AKS / container platforms, GPU infrastructure, data/analytics (e.g. Databricks-style patterns on Azure), and core Azure storage/networking dependencies. Align ANF's AI story with Azure-wide AI data guidance and reference architectures, and feed real customer workload evidence back into joint planning. Cross-functional leadership Lead across engineering, product marketing, sales, customer success, and professional services to ship capabilities and repeatable reference architectures / proof points. Engage strategic customers and design partners to validate pain, quantify value, and de-risk roadmap bets. Market intelligence & evangelism Monitor AI infrastructure trends (models, frameworks, orchestration, data formats) and competitor moves; translate into differentiated bets. Represent ANF as a credible technical executive in briefings, advisory councils, and industry forums. Industry segmentation Tailor AI storage strategy for segments where file semantics and performance matter, for example: semiconductor/EDA, manufacturing, healthcare imaging, financial services, energy, media & entertainment, and HPC/simulation-including compliance and data residency realities. Job Requirements Required 10+ years product management in cloud infrastructure, enterprise storage, AI/ML infrastructure, or data platforms (principal scope: portfolio strategy, multi-team alignment, executive storytelling). Strong command of enterprise storage: NFS/SMB semantics, snapshots/clones, replication, backup integration patterns, capacity/performance tiers, and large-scale filesystem behavior under parallel workloads. Hands-on familiarity with modern AI stacks: LLMs, RAG architectures, embeddings/vector retrieval patterns, training vs. inference IO profiles, orchestration, and enterprise AI data pipelines. Demonstrated success influencing engineering and partner roadmaps without direct authority; experience with hyperscaler first-party or deeply partnered services is a strong plus. Excellent written and verbal communication to customers, executives, and engineers. Preferred Direct experience with Microsoft Azure AI services, GPU estates on Azure, and/or Azure Kubernetes Service + ML platform integrations. Familiarity with Databricks, Iceberg/Delta-class open table patterns, Kubernetes storage patterns, NVIDIA AI software stacks, and enterprise MLOps release cadences. Background in regulated industries and enterprise security/governance requirements for AI data. Education MBA or advanced degree in CS/Engineering (helpful, not a substitute for demonstrated technical depth). Compensation: The target salary range for this position is $228,000 - $325,000. The salary offered will be determined by the candidate's location, qualifications, experience, and education and may be outside of this range. Final compensation packages are competitive and in line with industry standards, reflecting a variety of factors, and include a comprehensive benefits package. This may cover Health Insurance, Life Insurance, Retirement or Pension Plans, Paid Time Off, various Leave options, Performance-Based Incentives, employee stock purchase plan, and/or restricted stocks (RSU's), with all offerings subject to regional variations and governed by local laws, regulations, and company policies. Benefits may vary by country and region, and further details will be provided as part of the recruitment process. At NetApp, we embrace a hybrid working environment designed to strengthen connection, collaboration, and culture for all employees. This means that most roles will have some level of in-office and/or in-person expectations, which will be shared during the recruitment process. Equal Opportunity Employer: NetApp is firmly committed to Equal Employment Opportunity (EEO) and to compliance with all federal . click apply for full job details

Own Every Moment at NetApp At NetApp, your ideas power innovation. We lead in intelligent data infrastructure-delivering unified storage, integrated data services, and solutions that help organizations unlock the full potential of their data, from AI to multicloud. Ready to innovate and contribute to our path to $10B? Here, you'll collaborate with passionate teams, tackle real-world challenges, and see your impact in how customers transform and grow. If you're ready to bring curiosity, creativity, and drive to every moment, NetApp is where your journey begins. Job Summary We are seeking a Principal Product Manager to lead the definition and evolution of NetApp's AI Data Infrastructure (AIDI) portfolio. This role owns a broad, end to end AI infrastructure strategy, spanning ONTAP based data services delivered across multiple hardware platforms, integrated systems, reference architectures, and full stack AI solutions. This PM operates at the center of NetApp's most strategic AI initiatives-working closely with architecture, engineering, and strategic technology partners-to define scalable, repeatable, and monetizable AI data platforms. The role focuses on enabling ONTAP and complementary data services across diverse system architectures, including high performance file and block platforms, scale out systems, and object storage, as well as validated reference architectures. The role supports both Neocloud providers and Strategic Enterprise customers, shaping solutions that enable training, fine tuning, inference, and emerging AI workloads across hybrid and on prem environments. Job Responsibilities AI Data Infrastructure Strategy & Vision Define and own the holistic AIDI product strategy, centered on ONTAP based data services delivered across multiple hardware platforms, integrated systems, reference designs, and full solution architectures. Develop a phased AIDI roadmap, clearly articulating MVP capabilities, platform extensions, and long term architectural evolution. Identify and prioritize AI workload use cases (training, fine tuning, inference, multi tenant AI platforms), and map them to storage platforms, data services, and deployment models. Reference Architectures & Partner Ecosystem Lead co development and integration efforts with strategic technology partners, spanning compute, accelerator, networking, and platform ecosystems. Define, productize, and maintain validated reference architectures and certified AI designs (e.g., clustered AI platforms, modular AI stacks), ensuring they are repeatable, supportable, and field ready. Act as the product interface between NetApp storage platforms (ONTAP based systems, E Series, StorageGRID) and external partner ecosystems. Platform & Ecosystem Definition Drive platform and system architecture decisions, including storage platforms, interconnects, and system level tradeoffs, in close partnership with architecture and engineering. Define end to end AI infrastructure solutions, combining multiple storage platforms, data services, lifecycle management, and operational integration-not just standalone components. Evaluate and define fulfillment and delivery models, including: Meet in the channel offerings OEM and ODM based solutions Integrated and validated system offerings Customer, Market & Business Requirements Gather and synthesize requirements from Neocloud providers and large enterprise customers, addressing performance, scale, multi tenancy, and operational simplicity. Translate customer needs into clear product requirements, differentiated value propositions, and business cases. Partner with GTM, sales, and field teams to ensure offerings are consumable, supportable, and aligned with real world deployment models. Monetization & Business Models Define monetization strategies for AIDI offerings, including software licensing, subscriptions, consumption based models, and bundled platform offerings. Partner with finance and GTM teams to assess revenue impact, pricing, margin, and cost structure across solution types. Cross Functional Leadership Serve as the single point of accountability across architecture, engineering, sales, marketing, alliances, and operations for AIDI. Communicate strategy, architectural tradeoffs, and roadmap clearly to executive leadership and field organizations. Influence long term platform decisions that impact multiple product lines and business units. Job Requirements 15+ years of product management experience with enterprise infrastructure, storage platforms, or cloud adjacent systems. Strong understanding of on prem and/or cloud infrastructure and modern data center architectures. Proven experience partnering with architecture and engineering teams to translate technical concepts into market ready products. Experience defining product roadmaps, phased releases, and go to market strategies. Preferred Experience working with hyperscalers, Neocloud providers, or large enterprise customers. Familiarity with OEM/ODM ecosystems, multi vendor platforms, and channel based delivery models. Background in defining monetization and licensing models for software, platforms, or integrated solutions. Why This Role Matters This role is critical to shaping the future of our AI Data Infrastructure business. You'll influence core architectural decisions, unlock new revenue opportunities, and position NetApp as a leader in AI ready data platforms and solutions, while working closely with senior leaders across the company. Education IC - Typically requires a minimum of 15 years of related experience.Mgr & Exec - Typically requires a minimum of 10 years of related experience. Compensation: The target salary range for this position is 227,800 - 338,800 USD. The salary offered will be determined by the candidate's location, qualifications, experience, and education and may be outside of this range. The range is based on 'On Target Earnings' (OTE) representing the total potential earnings, which is the sum of the base salary and potential commission earned when performance targets are achieved. Final compensation packages are competitive and in line with industry standards, reflecting a variety of factors, and include a comprehensive benefits package. This may cover Health Insurance, Life Insurance, Retirement or Pension Plans, Paid Time Off, various Leave options, employee stock purchase plan, and/or restricted stocks (RSU's). These offerings are subject to regional variations and governed by local laws, regulations, and company policies. We will provide detailed information about the specific benefits for your region during the recruitment process. At NetApp, we embrace a hybrid working environment designed to strengthen connection, collaboration, and culture for all employees. This means that most roles will have some level of in-office and/or in-person expectations, which will be shared during the recruitment process. Equal Opportunity Employer: NetApp is firmly committed to Equal Employment Opportunity (EEO) and to compliance with all federal, state and local laws that prohibit employment discrimination based on age, race, color, gender, sexual orientation, gender identity, national origin, religion, disability or genetic information, pregnancy, protected veteran status, and any other protected classification. Why You'll Thrive at NetApp At NetApp, you won't wait for the perfect moment-you'll make it. The early planning, the extra thought, the bold idea that turns good into great: That's how our people operate and how we continue to push the boundaries of data infrastructure. NetApp is the trusted partner for organizations transforming data into opportunity. As the only enterprise-grade storage service natively embedded in Google Cloud, AWS, and Microsoft Azure, we empower customers to run everything from traditional workloads to enterprise AI with unmatched performance, resilience, and security. Our culture We celebrate mold breakers, bold thinkers, and problem solvers. We reward initiative, impact, and ownership. We provide flexibility so you can balance professional ambition with your personal life. Here, differences are not just welcomed-they drive everything we do. If you're ready to innovate, rise to the challenge, and own every moment - make your next move your best one. Apply now.

Own Every Moment at NetApp At NetApp, your ideas power innovation. We lead in intelligent data infrastructure-delivering unified storage, integrated data services, and solutions that help organizations unlock the full potential of their data, from AI to multicloud. Ready to innovate and contribute to our path to $10B? Here, you'll collaborate with passionate teams, tackle real-world challenges, and see your impact in how customers transform and grow. If you're ready to bring curiosity, creativity, and drive to every moment, NetApp is where your journey begins. Job Summary NetApp is hiring a principal-level product leader to own the AI product strategy for Azure NetApp Files (ANF)-a first-party, fully managed enterprise file service on Microsoft Azure, delivered in deep partnership between NetApp and Microsoft. In the spirit of NetApp's "business builder" cloud roles, you will translate a fast-moving AI landscape into differentiated platform capabilities, joint roadmap bets with Microsoft, and enterprise outcomes (performance, data locality, governance, and time-to-value for AI pipelines). You will sit at the intersection of enterprise storage, Azure AI infrastructure, and industry AI workloads, ensuring ANF is positioned and built as a strategic data foundation for training, inference, RAG, analytics, simulation, and agentic workflows-without forcing customers to abandon enterprise file semantics, protection, or hybrid operating models. Role Overview We need a highly strategic and deeply technical principal PM who can: Define multi-year AI vision and roadmap for ANF in the context of Azure AI services, GPU estates, data platforms, and regulated enterprise environments. Turn emerging patterns (LLMs, RAG, agents, orchestration, multimodal data, vector retrieval, high-throughput checkpointing) into concrete product requirements and joint go-to-market narratives with Microsoft. Balance hyperscaler co-development constraints with NetApp differentiation (enterprise data services, multiprotocol access, lifecycle management, resiliency, and cross-cloud consistency where relevant). Responsibilities AI strategy & roadmap Own end-to-end AI strategy for ANF: problem selection, success metrics, phased delivery, and competitive positioning vs. other Azure and AI-native storage options. Prioritize investments across performance, scale, data services, protocol and API surfaces, and operational excellence for AI pipelines. Workload-led product definition Drive requirements for AI-centric scenarios, including: Training and inference data planes (high throughput, low latency, checkpointing, bursty I/O) RAG and enterprise search (datasets, versioning, clones, refresh patterns) Agentic workflows and orchestration (durable shared state, tool/data access patterns-where productized responsibly) Large multimodal and enterprise datasets (governance, access control, lifecycle) Analytics and simulation adjacencies (HPC/EDA-style throughput, shared filesystem semantics) Hyperscaler & ecosystem partnership Partner with Microsoft teams across Azure AI / Foundry, Azure Machine Learning, AKS / container platforms, GPU infrastructure, data/analytics (e.g. Databricks-style patterns on Azure), and core Azure storage/networking dependencies. Align ANF's AI story with Azure-wide AI data guidance and reference architectures, and feed real customer workload evidence back into joint planning. Cross-functional leadership Lead across engineering, product marketing, sales, customer success, and professional services to ship capabilities and repeatable reference architectures / proof points. Engage strategic customers and design partners to validate pain, quantify value, and de-risk roadmap bets. Market intelligence & evangelism Monitor AI infrastructure trends (models, frameworks, orchestration, data formats) and competitor moves; translate into differentiated bets. Represent ANF as a credible technical executive in briefings, advisory councils, and industry forums. Industry segmentation Tailor AI storage strategy for segments where file semantics and performance matter, for example: semiconductor/EDA, manufacturing, healthcare imaging, financial services, energy, media & entertainment, and HPC/simulation-including compliance and data residency realities. AI strategy & roadmap Own end-to-end AI strategy for ANF: problem selection, success metrics, phased delivery, and competitive positioning vs. other Azure and AI-native storage options. Prioritize investments across performance, scale, data services, protocol and API surfaces, and operational excellence for AI pipelines. Workload-led product definition Drive requirements for AI-centric scenarios, including: Training and inference data planes (high throughput, low latency, checkpointing, bursty I/O) RAG and enterprise search (datasets, versioning, clones, refresh patterns) Agentic workflows and orchestration (durable shared state, tool/data access patterns-where productized responsibly) Large multimodal and enterprise datasets (governance, access control, lifecycle) Analytics and simulation adjacencies (HPC/EDA-style throughput, shared filesystem semantics) Hyperscaler & ecosystem partnership Partner with Microsoft teams across Azure AI / Foundry, Azure Machine Learning, AKS / container platforms, GPU infrastructure, data/analytics (e.g. Databricks-style patterns on Azure), and core Azure storage/networking dependencies. Align ANF's AI story with Azure-wide AI data guidance and reference architectures, and feed real customer workload evidence back into joint planning. Cross-functional leadership Lead across engineering, product marketing, sales, customer success, and professional services to ship capabilities and repeatable reference architectures / proof points. Engage strategic customers and design partners to validate pain, quantify value, and de-risk roadmap bets. Market intelligence & evangelism Monitor AI infrastructure trends (models, frameworks, orchestration, data formats) and competitor moves; translate into differentiated bets. Represent ANF as a credible technical executive in briefings, advisory councils, and industry forums. Industry segmentation Tailor AI storage strategy for segments where file semantics and performance matter, for example: semiconductor/EDA, manufacturing, healthcare imaging, financial services, energy, media & entertainment, and HPC/simulation-including compliance and data residency realities. Job Requirements Required 10+ years product management in cloud infrastructure, enterprise storage, AI/ML infrastructure, or data platforms (principal scope: portfolio strategy, multi-team alignment, executive storytelling). Strong command of enterprise storage: NFS/SMB semantics, snapshots/clones, replication, backup integration patterns, capacity/performance tiers, and large-scale filesystem behavior under parallel workloads. Hands-on familiarity with modern AI stacks: LLMs, RAG architectures, embeddings/vector retrieval patterns, training vs. inference IO profiles, orchestration, and enterprise AI data pipelines. Demonstrated success influencing engineering and partner roadmaps without direct authority; experience with hyperscaler first-party or deeply partnered services is a strong plus. Excellent written and verbal communication to customers, executives, and engineers. Preferred Direct experience with Microsoft Azure AI services, GPU estates on Azure, and/or Azure Kubernetes Service + ML platform integrations. Familiarity with Databricks, Iceberg/Delta-class open table patterns, Kubernetes storage patterns, NVIDIA AI software stacks, and enterprise MLOps release cadences. Background in regulated industries and enterprise security/governance requirements for AI data. Education MBA or advanced degree in CS/Engineering (helpful, not a substitute for demonstrated technical depth). Compensation: The target salary range for this position is $228,000 - $325,000. The salary offered will be determined by the candidate's location, qualifications, experience, and education and may be outside of this range. Final compensation packages are competitive and in line with industry standards, reflecting a variety of factors, and include a comprehensive benefits package. This may cover Health Insurance, Life Insurance, Retirement or Pension Plans, Paid Time Off, various Leave options, Performance-Based Incentives, employee stock purchase plan, and/or restricted stocks (RSU's), with all offerings subject to regional variations and governed by local laws, regulations, and company policies. Benefits may vary by country and region, and further details will be provided as part of the recruitment process. At NetApp, we embrace a hybrid working environment designed to strengthen connection, collaboration, and culture for all employees. This means that most roles will have some level of in-office and/or in-person expectations, which will be shared during the recruitment process. Equal Opportunity Employer: NetApp is firmly committed to Equal Employment Opportunity (EEO) and to compliance with all federal . click apply for full job details

Requisition ID # 171393 Job Category: Business Operations / Strategy Job Level: Manager/Principal Business Unit: Energy Delivery Work Type: Hybrid Job Location: Oakland Department Overview The Procurement Organization includes a staff of more than two hundred sourcing managers, buyers, analysts, and supplier diversity personnel. Our mission is to deliver cost effective and valued procurement services through strategic, diverse, and sustainable business solutions. Our work requires close integration with all lines of business, finance, and our suppliers. The Procurement Excellence Center (PEC) is a strategic function dedicated to driving procurement transformation, operational efficiency, and value creation across the organization. Within the Procurement organization, the PEC establishes best practices, standardizes processes, and leverages advanced analytics and market intelligence to enable data-driven decision-making. The PEC collaborates with all Procurement teams to enhance capabilities, improve performance, and optimize costs. Key focus areas include market intelligence and analytics, digital procurement transformation, risk management, supplier relationship management, governance, and capability development. Position Summary The Principal Operations Data Analyst drives advanced analytics and modeling efforts to support strategic, data driven decisions across PG&E's Procurement Excellence Center. The role leads complex initiatives that enhance procurement performance, operational efficiency, and cost optimization. This role is accountable for identifying, prioritizing, and deploying AI use cases across Procurement and Supply Chain, from problem framing through production deployment and value realization. The Principal Operations Data Analyst acts as a bridge between business, digital, and IT teams to operationalize AI solutions that improve productivity, reduce cost, manage risk, and enhance supplier collaboration. This position is hybrid, working from your remote office and Oakland based on business needs or company requirements. PG&E is providing the full salary/pay range for this position. The actual amount paid to an individual will be based on multiple factors, including, but not limited to, internal equity, specific skills, education, licenses or certifications, experience, market value, and geographic location. The range to reasonably expect will be around the minimum and the midpoint . The final decision will be made on a case-by-case basis related to the factors above. This job is also eligible to participate in PG&E's discretionary incentive compensation programs. Bay Area Min: $140,000 Bay Area Mid: $ 189,000 Bay Area Max: $ 238,000 Reporting Relationship The Principal Operations Data Analyst will report to the Sr Director, Procurement Excellence Center. Job Responsibilities Owns the end to end lifecycle of AI use cases across Source to Pay and Supply Chain, including ideation, business case development, pilot execution, scaling, and sustained adoption. Partners with Procurement, Supply Chain, IT, Digital, and Data teams to translate business problems into deployable AI solutions. Measures and communicates realized value (cost savings, cycle time reduction, risk mitigation, productivity gains) from AI deployments. Leads the design and deployment of agentic AI and intelligent automation solutions across Source to Pay and Supply Chain processes, including sourcing, contracting, buying, supplier management, and fulfillment. Acts as a thought leader applying extensive data processing and data analysis expertise in the development of strategy or resolution to complex data issues. Creates very complex automated data routines and processes for reporting and data delivery ensuring accurate data manipulation and data cleansing. Applies advanced analytics and data engineering techniques to support AI- driven decision making Presents/communicates clear, concise and actionable data analyses for clients. Acts as team lead and provides direction to less experienced employees. May work with Senior Management to develop business related strategy, leveraging data in decision making. Ensures data quality, governance, and traceability across integrated tools and analytical models. Background Qualifications Minimum BA/BS Degree in Marketing, Business, Computer Science, Engineering or other related field or equivalent work experience 8 Years related work experience Desired 6 Years in Supply Chain and Procurement as a data analyst or a data scientist Masters Degree Hands on experience deploying machine learning, generative AI, or agent based systems into production business workflows for Supply chain Experience operationalizing AI solutions within enterprise platforms (e.g., SAP, Ariba, or adjacent procurement technologies). Familiarity with utility operations. Understanding of SAP and Ariba Ability to influence senior leaders and drive adoption of AI enabled ways of working. Advanced skill in writing SQL queries using Oracle or Business Objects Expertise in project management to lead large, cross functional projects and develop concise data findings for Sr. Management.

Own Every Moment at NetApp At NetApp, your ideas power innovation. We lead in intelligent data infrastructure-delivering unified storage, integrated data services, and solutions that help organizations unlock the full potential of their data, from AI to multicloud. Ready to innovate and contribute to our path to $10B? Here, you'll collaborate with passionate teams, tackle real-world challenges, and see your impact in how customers transform and grow. If you're ready to bring curiosity, creativity, and drive to every moment, NetApp is where your journey begins. Job Summary NetApp is hiring a principal-level product leader to own the AI product strategy for Azure NetApp Files (ANF)-a first-party, fully managed enterprise file service on Microsoft Azure, delivered in deep partnership between NetApp and Microsoft. In the spirit of NetApp's "business builder" cloud roles, you will translate a fast-moving AI landscape into differentiated platform capabilities, joint roadmap bets with Microsoft, and enterprise outcomes (performance, data locality, governance, and time-to-value for AI pipelines). You will sit at the intersection of enterprise storage, Azure AI infrastructure, and industry AI workloads, ensuring ANF is positioned and built as a strategic data foundation for training, inference, RAG, analytics, simulation, and agentic workflows-without forcing customers to abandon enterprise file semantics, protection, or hybrid operating models. Role Overview We need a highly strategic and deeply technical principal PM who can: Define multi-year AI vision and roadmap for ANF in the context of Azure AI services, GPU estates, data platforms, and regulated enterprise environments. Turn emerging patterns (LLMs, RAG, agents, orchestration, multimodal data, vector retrieval, high-throughput checkpointing) into concrete product requirements and joint go-to-market narratives with Microsoft. Balance hyperscaler co-development constraints with NetApp differentiation (enterprise data services, multiprotocol access, lifecycle management, resiliency, and cross-cloud consistency where relevant). Responsibilities AI strategy & roadmap Own end-to-end AI strategy for ANF: problem selection, success metrics, phased delivery, and competitive positioning vs. other Azure and AI-native storage options. Prioritize investments across performance, scale, data services, protocol and API surfaces, and operational excellence for AI pipelines. Workload-led product definition Drive requirements for AI-centric scenarios, including: Training and inference data planes (high throughput, low latency, checkpointing, bursty I/O) RAG and enterprise search (datasets, versioning, clones, refresh patterns) Agentic workflows and orchestration (durable shared state, tool/data access patterns-where productized responsibly) Large multimodal and enterprise datasets (governance, access control, lifecycle) Analytics and simulation adjacencies (HPC/EDA-style throughput, shared filesystem semantics) Hyperscaler & ecosystem partnership Partner with Microsoft teams across Azure AI / Foundry, Azure Machine Learning, AKS / container platforms, GPU infrastructure, data/analytics (e.g. Databricks-style patterns on Azure), and core Azure storage/networking dependencies. Align ANF's AI story with Azure-wide AI data guidance and reference architectures, and feed real customer workload evidence back into joint planning. Cross-functional leadership Lead across engineering, product marketing, sales, customer success, and professional services to ship capabilities and repeatable reference architectures / proof points. Engage strategic customers and design partners to validate pain, quantify value, and de-risk roadmap bets. Market intelligence & evangelism Monitor AI infrastructure trends (models, frameworks, orchestration, data formats) and competitor moves; translate into differentiated bets. Represent ANF as a credible technical executive in briefings, advisory councils, and industry forums. Industry segmentation Tailor AI storage strategy for segments where file semantics and performance matter, for example: semiconductor/EDA, manufacturing, healthcare imaging, financial services, energy, media & entertainment, and HPC/simulation-including compliance and data residency realities. AI strategy & roadmap Own end-to-end AI strategy for ANF: problem selection, success metrics, phased delivery, and competitive positioning vs. other Azure and AI-native storage options. Prioritize investments across performance, scale, data services, protocol and API surfaces, and operational excellence for AI pipelines. Workload-led product definition Drive requirements for AI-centric scenarios, including: Training and inference data planes (high throughput, low latency, checkpointing, bursty I/O) RAG and enterprise search (datasets, versioning, clones, refresh patterns) Agentic workflows and orchestration (durable shared state, tool/data access patterns-where productized responsibly) Large multimodal and enterprise datasets (governance, access control, lifecycle) Analytics and simulation adjacencies (HPC/EDA-style throughput, shared filesystem semantics) Hyperscaler & ecosystem partnership Partner with Microsoft teams across Azure AI / Foundry, Azure Machine Learning, AKS / container platforms, GPU infrastructure, data/analytics (e.g. Databricks-style patterns on Azure), and core Azure storage/networking dependencies. Align ANF's AI story with Azure-wide AI data guidance and reference architectures, and feed real customer workload evidence back into joint planning. Cross-functional leadership Lead across engineering, product marketing, sales, customer success, and professional services to ship capabilities and repeatable reference architectures / proof points. Engage strategic customers and design partners to validate pain, quantify value, and de-risk roadmap bets. Market intelligence & evangelism Monitor AI infrastructure trends (models, frameworks, orchestration, data formats) and competitor moves; translate into differentiated bets. Represent ANF as a credible technical executive in briefings, advisory councils, and industry forums. Industry segmentation Tailor AI storage strategy for segments where file semantics and performance matter, for example: semiconductor/EDA, manufacturing, healthcare imaging, financial services, energy, media & entertainment, and HPC/simulation-including compliance and data residency realities. Job Requirements Required 10+ years product management in cloud infrastructure, enterprise storage, AI/ML infrastructure, or data platforms (principal scope: portfolio strategy, multi-team alignment, executive storytelling). Strong command of enterprise storage: NFS/SMB semantics, snapshots/clones, replication, backup integration patterns, capacity/performance tiers, and large-scale filesystem behavior under parallel workloads. Hands-on familiarity with modern AI stacks: LLMs, RAG architectures, embeddings/vector retrieval patterns, training vs. inference IO profiles, orchestration, and enterprise AI data pipelines. Demonstrated success influencing engineering and partner roadmaps without direct authority; experience with hyperscaler first-party or deeply partnered services is a strong plus. Excellent written and verbal communication to customers, executives, and engineers. Preferred Direct experience with Microsoft Azure AI services, GPU estates on Azure, and/or Azure Kubernetes Service + ML platform integrations. Familiarity with Databricks, Iceberg/Delta-class open table patterns, Kubernetes storage patterns, NVIDIA AI software stacks, and enterprise MLOps release cadences. Background in regulated industries and enterprise security/governance requirements for AI data. Education MBA or advanced degree in CS/Engineering (helpful, not a substitute for demonstrated technical depth). Compensation: The target salary range for this position is $228,000 - $325,000. The salary offered will be determined by the candidate's location, qualifications, experience, and education and may be outside of this range. Final compensation packages are competitive and in line with industry standards, reflecting a variety of factors, and include a comprehensive benefits package. This may cover Health Insurance, Life Insurance, Retirement or Pension Plans, Paid Time Off, various Leave options, Performance-Based Incentives, employee stock purchase plan, and/or restricted stocks (RSU's), with all offerings subject to regional variations and governed by local laws, regulations, and company policies. Benefits may vary by country and region, and further details will be provided as part of the recruitment process. At NetApp, we embrace a hybrid working environment designed to strengthen connection, collaboration, and culture for all employees. This means that most roles will have some level of in-office and/or in-person expectations, which will be shared during the recruitment process. Equal Opportunity Employer: NetApp is firmly committed to Equal Employment Opportunity (EEO) and to compliance with all federal . click apply for full job details

Principal Data Scientist, AI Foundations Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making. As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives. Team Description AI Foundations Specialist Models Data Science team builds and ships state of the art scalable architecture, AI/ML solutions for Capital One's award-winning mobile app. We partner with product, tech and design teams to deliver app features that delight customers with dynamic and personalized experiences, enable them to chat with Capital One's digital assistant Eno, or search for useful contents. You will be the driving force to experiment, innovate and create next generation experiences powered by the latest emerging generative AI technologies. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI powered products that change how customers interact with their money. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Be the expert in Natural Language Processing (NLP) to harness the power of Large Language Models (LLMs), adapt and finetune them for customer facing applications and features. Build machine learning and NLP models through all phases of development, from design through training, evaluation, and validation; partnering with engineering teams to operationalize them in scalable and resilient production systems that serve 80+ million customers. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate is: Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. Technical. You're comfortable with advanced ML and DL technologies including language models and are passionate about developing further. You have hands-on experience working with LLMs and solutions using open-source tools and cloud computing platforms. Influential. You are passionate about AI/ML and can bring along a cross functional team in breakthrough innovations. You communicate clearly and effectively to share your findings with non-technical audiences. You are experienced in training language models or large computer vision models as well as have expertise in one or more key subdomains such as: training optimization, self-supervised learning, explainability, RLHF. You have an engineering mindset as shown by a track record of delivering models at scale both in training data and inference volumes. You have experience in delivering libraries, platforms, or solution level code to existing products. Basic Qualifications: Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 5 years of experience performing data analytics A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 3 years of experience performing data analytics A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) Preferred Qualifications: Master's Degree in "STEM" field (Science, Technology, Engineering, or Mathematics), or PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) Experience working with AWS At least 3 years' experience in Python, Scala, or R At least 3 years' experience with machine learning At least 3 years' experience with SQL 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: $158,600 - $181,000 for Princ Associate, Data Science New York, NY: $173,000 - $197,400 for Princ Associate, Data Science San Jose, CA: $173,000 - $197,400 for Princ Associate, Data Science 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. Distinguished AI Engineer (Agentic AI Platform) 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. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. You will contribute to the north star platform architecture, continuously publishing and refining living diagrams and canonical APIs that cover agent orchestration, RAG pipelines, prompt libraries and multi-tenant policy enforcement. A major emphasis is around standardizing and automating agentic workflows : you will evaluate agentic frameworks such LangGraph, AutoGen, Semantic Kernal, CrewAI and LlamaIndex and then harden / blend patterns that best meet enterprise SLAs do that 90% of new apps adopt them. Developer experience is another cornerstone. You will contribute to crafting an end to end GenAI SDK, CLI and starter kits that let AI engineers spin up secure, observable agentic workflows in under minutes, shrinking prototyping to production timelines by 30%. Trust and safety remain paramount; you will help bring together a vision of central guardrail services - prompt firewalls, content-filter hooks, red team harnesses and audit APIs - consumed by every application to ensure zero Sev4 incidents. You will collaborate with cross organization architects to drive end to end performance by optimizing orchestration - level batching, retrieval caching, heuristic tuning to achieve reductions in per token spend. You will accelerate innovation by incubating proof of concepts and driving RFCs such as hierarchical agent memory, multimodal guardrails, multimodal RAG. You'll own central Helm charts, operators and CRDs that auto scale agents to hit tenant SLAs Finally you will coach and evangelize - hosting architecture office hours, mentoring Staff, Principal and Senior engineers, authoring technical design documents and blogs and representing Capital One at Tier1 AI conferences - to amplify platform vision across internal and external communities. 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, Engineering, or AI plus at least 10 years of experience developing AI and ML algorithms or technologies, or Master's degree plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) 2+ years of experience supporting Agentic Frameworks (LangChain, CrewAI, Semantic Kernel (Microsoft), or AutoGen) 2+ years of experience with LLMOps (Google Cloud Vertex AI, Amazon SageMaker, Azure Machine Learning) 8+ years of experience designing mission-critical machine learning platforms 2+ years of experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level 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 Master's degree in Computer Science, Computer Engineering, or relevant technical field Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience leading GenAI or LLM-Powered application architectures in production Deep understanding of Responsible AI, data privacy and multi-tenant security patterns K8s mastery (multi-region clusters, service mesh) Experience staying abreast of the latest AI research and AI systems and applying novel techniques in production 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: $314,800 - $359,300 for Sr. Distinguished AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Distinguished AI Engineer New York, NY: $343,400 - $392,000 for Sr. Distinguished AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Distinguished AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Distinguished 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 . click apply for full job details

Principal Data Scientist, AI Foundations Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making. As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives. Team Description AI Foundations Specialist Models Data Science team builds and ships state of the art scalable architecture, AI/ML solutions for Capital One's award-winning mobile app. We partner with product, tech and design teams to deliver app features that delight customers with dynamic and personalized experiences, enable them to chat with Capital One's digital assistant Eno, or search for useful contents. You will be the driving force to experiment, innovate and create next generation experiences powered by the latest emerging generative AI technologies. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI powered products that change how customers interact with their money. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Be the expert in Natural Language Processing (NLP) to harness the power of Large Language Models (LLMs), adapt and finetune them for customer facing applications and features. Build machine learning and NLP models through all phases of development, from design through training, evaluation, and validation; partnering with engineering teams to operationalize them in scalable and resilient production systems that serve 80+ million customers. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate is: Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. Technical. You're comfortable with advanced ML and DL technologies including language models and are passionate about developing further. You have hands-on experience working with LLMs and solutions using open-source tools and cloud computing platforms. Influential. You are passionate about AI/ML and can bring along a cross functional team in breakthrough innovations. You communicate clearly and effectively to share your findings with non-technical audiences. You are experienced in training language models or large computer vision models as well as have expertise in one or more key subdomains such as: training optimization, self-supervised learning, explainability, RLHF. You have an engineering mindset as shown by a track record of delivering models at scale both in training data and inference volumes. You have experience in delivering libraries, platforms, or solution level code to existing products. Basic Qualifications: Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 5 years of experience performing data analytics A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 3 years of experience performing data analytics A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) Preferred Qualifications: Master's Degree in "STEM" field (Science, Technology, Engineering, or Mathematics), or PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) Experience working with AWS At least 3 years' experience in Python, Scala, or R At least 3 years' experience with machine learning At least 3 years' experience with SQL 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: $158,600 - $181,000 for Princ Associate, Data Science New York, NY: $173,000 - $197,400 for Princ Associate, Data Science San Jose, CA: $173,000 - $197,400 for Princ Associate, Data Science 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. Distinguished AI Engineer (Agentic AI Platform) 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. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. You will contribute to the north star platform architecture, continuously publishing and refining living diagrams and canonical APIs that cover agent orchestration, RAG pipelines, prompt libraries and multi-tenant policy enforcement. A major emphasis is around standardizing and automating agentic workflows : you will evaluate agentic frameworks such LangGraph, AutoGen, Semantic Kernal, CrewAI and LlamaIndex and then harden / blend patterns that best meet enterprise SLAs do that 90% of new apps adopt them. Developer experience is another cornerstone. You will contribute to crafting an end to end GenAI SDK, CLI and starter kits that let AI engineers spin up secure, observable agentic workflows in under minutes, shrinking prototyping to production timelines by 30%. Trust and safety remain paramount; you will help bring together a vision of central guardrail services - prompt firewalls, content-filter hooks, red team harnesses and audit APIs - consumed by every application to ensure zero Sev4 incidents. You will collaborate with cross organization architects to drive end to end performance by optimizing orchestration - level batching, retrieval caching, heuristic tuning to achieve reductions in per token spend. You will accelerate innovation by incubating proof of concepts and driving RFCs such as hierarchical agent memory, multimodal guardrails, multimodal RAG. You'll own central Helm charts, operators and CRDs that auto scale agents to hit tenant SLAs Finally you will coach and evangelize - hosting architecture office hours, mentoring Staff, Principal and Senior engineers, authoring technical design documents and blogs and representing Capital One at Tier1 AI conferences - to amplify platform vision across internal and external communities. 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, Engineering, or AI plus at least 10 years of experience developing AI and ML algorithms or technologies, or Master's degree plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) 2+ years of experience supporting Agentic Frameworks (LangChain, CrewAI, Semantic Kernel (Microsoft), or AutoGen) 2+ years of experience with LLMOps (Google Cloud Vertex AI, Amazon SageMaker, Azure Machine Learning) 8+ years of experience designing mission-critical machine learning platforms 2+ years of experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level 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 Master's degree in Computer Science, Computer Engineering, or relevant technical field Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience leading GenAI or LLM-Powered application architectures in production Deep understanding of Responsible AI, data privacy and multi-tenant security patterns K8s mastery (multi-region clusters, service mesh) Experience staying abreast of the latest AI research and AI systems and applying novel techniques in production 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: $314,800 - $359,300 for Sr. Distinguished AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Distinguished AI Engineer New York, NY: $343,400 - $392,000 for Sr. Distinguished AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Distinguished AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Distinguished 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 . click apply for full job details

Principal Associate, Data Scientist - Mainstreet Acquisitions Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making. As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives. Team Description Valuations team is a multi-disciplinary team focused on the development, deployment, model governance, and risk management of valuations model in credit underwriting. Our mission is to bring real-time, personalized offers to our customers - via innovation and optimization in our valuations modeling system. We work with partners from across the enterprise to build data and modeling products that enable best in class credit analysis and customer-facing decisioning. Underwriting innovation is a key source of Capital One's competitive advantage - it is in our DNA. Our team continues to push that competitive edge through the use of new data and advanced modeling techniques. Building the capabilities that the enterprise needs is a challenging long term project; the prize is big and there are plenty of opportunities to deliver value on the way. To bring our vision to life, as a model developer and data scientist, you can expect to: Conduct model development, experimenting with various statistical methodologies to improve model performance; Leverage alternative data sources along with various feature selection and engineering techniques to enhance in market models; Develop next-gen credit underwriting models; Partner with key stakeholders across the organization to establish standards for the new modeling approaches that are consistent with our values; Push the envelope with new data and new modeling approaches to improve our lending decisions. Our team's work is both intellectually demanding and highly collaborative. As part of an enterprise team delivering new capabilities, you will be working across: LOB underwriting teams, various DS/DA teams, enterprise platform teams, enterprise data team, tech teams, legal and compliance teams, consumer credit risk management, model risk office, and enterprise data risk management. Great team culture is profoundly important to us: we want everyone to feel they are doing meaningful and enjoyable work; we are informal and indifferent to hierarchy; we actively encourage new ideas and new ways of doing things; we respect each other's perspectives and preferences. Role Description In this role, you will: Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love Leverage a broad stack of technologies - Python, Conda, AWS, Spark, and more - to reveal the insights hidden within huge volumes of numeric and textual data Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation Flex your interpersonal skills to translate the complexity of your work into tangible business goals The Ideal Candidate is: Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms. Statistically-minded. You've built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning. A data guru. "Big data" doesn't faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science. Basic Qualifications: Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 5 years of experience performing data analytics A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 3 years of experience performing data analytics A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) Preferred Qualifications: Master's Degree in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) At least 1 year of experience working with AWS At least 3 years' experience in Python, Scala, or R At least 3 years' experience with machine learning At least 3 years' experience with SQL 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 Princ Associate, Data Science New York, NY: $176,500 - $201,400 for Princ Associate, Data Science 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).

Distinguished AI Engineer (Agentic AI Platform) 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. Why this Role Matters: We are building an enterprise Generative AI Platform that lets dozens of product teams compose powerful, safe and explainable AI capabilities - without wrestling with model minutiae or infra plumbing. You will design the agentic workflow framework, shared services such as memory, guardrails, vector search, SDKs and blueprints that translate foundation model power into production grade applications used by millions of users across multiple lines of businesses. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. You will contribute to the north star platform architecture, continuously publishing and refining living diagrams and canonical APIs that cover agent orchestration, RAG pipelines, prompt libraries and multi-tenant policy enforcement. A major emphasis is around standardizing and automating agentic workflows : you will evaluate agentic frameworks such LangGraph, AutoGen, Semantic Kernal, CrewAI and LlamaIndex and then harden / blend patterns that best meet enterprise SLAs do that 90% of new apps adopt them. Developer experience is another cornerstone. You will contribute to crafting an end to end GenAI SDK, CLI and starter kits that let AI engineers spin up secure, observable agentic workflows in under minutes, shrinking prototyping to production timelines by 30%. Trust and safety remain paramount; you will help bring together a vision of central guardrail services - prompt firewalls, content-filter hooks, red team harnesses and audit APIs - consumed by every application to ensure zero Sev4 incidents. You will collaborate with cross organization architects to drive end to end performance by optimizing orchestration - level batching, retrieval caching, heuristic tuning to achieve reductions in per token spend. You will accelerate innovation by incubating proof of concepts and driving RFCs such as hierarchical agent memory, multimodal guardrails, multimodal RAG. You'll own central Helm charts, operators and CRDs that auto scale agents to hit tenant SLAs Finally you will coach and evangelize - hosting architecture office hours, mentoring Staff, Principal and Senior engineers, authoring technical design documents and blogs and representing Capital One at Tier1 AI conferences - to amplify platform vision across internal and external communities. Basic Qualifications: Bachelor's degree in Computer Science, Engineering, or AI plus at least 8 years of experience developing AI and ML algorithms or technologies, or Master's degree plus at least 6 years of experience developing AI and ML algorithms or technologies At least 8 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 8+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) 2+ years of experience supporting Agentic Frameworks (LangChain, CrewAI, Semantic Kernel (Microsoft), or AutoGen) 2+ years of experience with LLMOps (Google Cloud Vertex AI, Amazon SageMaker, Azure Machine Learning) 8+ years of experience designing mission-critical machine learning platforms 2+ years of experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level 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 Master's degree in Computer Science, Computer Engineering, or relevant technical field Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience leading GenAI or LLM-Powered application architectures in production Deep understanding of Responsible AI, data privacy and multi-tenant security patterns Experience as a Staff-plus or Distinguished IC engineer influencing 50+ engineers and C-suite stakeholders K8s mastery (multi-region clusters, sericie mesh) Experience staying abreast of the latest AI research and AI systems and applying novel techniques in production Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $269,100 - $307,200 for Distinguished AI Engineer McLean, VA: $269,100 - $307,200 for Distinguished AI Engineer New York, NY: $293,600 - $335,100 for Distinguished AI Engineer San Francisco, CA: $293,600 - $335,100 for Distinguished AI Engineer San Jose, CA: $293,600 - $335,100 for Distinguished 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 . click apply for full job details

Distinguished AI Engineer (Agentic AI Platform) 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. Why this Role Matters: We are building an enterprise Generative AI Platform that lets dozens of product teams compose powerful, safe and explainable AI capabilities - without wrestling with model minutiae or infra plumbing. You will design the agentic workflow framework, shared services such as memory, guardrails, vector search, SDKs and blueprints that translate foundation model power into production grade applications used by millions of users across multiple lines of businesses. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. You will contribute to the north star platform architecture, continuously publishing and refining living diagrams and canonical APIs that cover agent orchestration, RAG pipelines, prompt libraries and multi-tenant policy enforcement. A major emphasis is around standardizing and automating agentic workflows : you will evaluate agentic frameworks such LangGraph, AutoGen, Semantic Kernal, CrewAI and LlamaIndex and then harden / blend patterns that best meet enterprise SLAs do that 90% of new apps adopt them. Developer experience is another cornerstone. You will contribute to crafting an end to end GenAI SDK, CLI and starter kits that let AI engineers spin up secure, observable agentic workflows in under minutes, shrinking prototyping to production timelines by 30%. Trust and safety remain paramount; you will help bring together a vision of central guardrail services - prompt firewalls, content-filter hooks, red team harnesses and audit APIs - consumed by every application to ensure zero Sev4 incidents. You will collaborate with cross organization architects to drive end to end performance by optimizing orchestration - level batching, retrieval caching, heuristic tuning to achieve reductions in per token spend. You will accelerate innovation by incubating proof of concepts and driving RFCs such as hierarchical agent memory, multimodal guardrails, multimodal RAG. You'll own central Helm charts, operators and CRDs that auto scale agents to hit tenant SLAs Finally you will coach and evangelize - hosting architecture office hours, mentoring Staff, Principal and Senior engineers, authoring technical design documents and blogs and representing Capital One at Tier1 AI conferences - to amplify platform vision across internal and external communities. Basic Qualifications: Bachelor's degree in Computer Science, Engineering, or AI plus at least 8 years of experience developing AI and ML algorithms or technologies, or Master's degree plus at least 6 years of experience developing AI and ML algorithms or technologies At least 8 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 8+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) 2+ years of experience supporting Agentic Frameworks (LangChain, CrewAI, Semantic Kernel (Microsoft), or AutoGen) 2+ years of experience with LLMOps (Google Cloud Vertex AI, Amazon SageMaker, Azure Machine Learning) 8+ years of experience designing mission-critical machine learning platforms 2+ years of experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level 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 Master's degree in Computer Science, Computer Engineering, or relevant technical field Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience leading GenAI or LLM-Powered application architectures in production Deep understanding of Responsible AI, data privacy and multi-tenant security patterns Experience as a Staff-plus or Distinguished IC engineer influencing 50+ engineers and C-suite stakeholders K8s mastery (multi-region clusters, sericie mesh) Experience staying abreast of the latest AI research and AI systems and applying novel techniques in production Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $269,100 - $307,200 for Distinguished AI Engineer McLean, VA: $269,100 - $307,200 for Distinguished AI Engineer New York, NY: $293,600 - $335,100 for Distinguished AI Engineer San Francisco, CA: $293,600 - $335,100 for Distinguished AI Engineer San Jose, CA: $293,600 - $335,100 for Distinguished 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 . click apply for full job details

Principal Data Scientist, AI Foundations Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making. As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives. Team Description AI Foundations Specialist Models Data Science team builds and ships state of the art scalable architecture, AI/ML solutions for Capital One's award-winning mobile app. We partner with product, tech and design teams to deliver app features that delight customers with dynamic and personalized experiences, enable them to chat with Capital One's digital assistant Eno, or search for useful contents. You will be the driving force to experiment, innovate and create next generation experiences powered by the latest emerging generative AI technologies. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI powered products that change how customers interact with their money. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Be the expert in Natural Language Processing (NLP) to harness the power of Large Language Models (LLMs), adapt and finetune them for customer facing applications and features. Build machine learning and NLP models through all phases of development, from design through training, evaluation, and validation; partnering with engineering teams to operationalize them in scalable and resilient production systems that serve 80+ million customers. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate is: Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. Technical. You're comfortable with advanced ML and DL technologies including language models and are passionate about developing further. You have hands-on experience working with LLMs and solutions using open-source tools and cloud computing platforms. Influential. You are passionate about AI/ML and can bring along a cross functional team in breakthrough innovations. You communicate clearly and effectively to share your findings with non-technical audiences. You are experienced in training language models or large computer vision models as well as have expertise in one or more key subdomains such as: training optimization, self-supervised learning, explainability, RLHF. You have an engineering mindset as shown by a track record of delivering models at scale both in training data and inference volumes. You have experience in delivering libraries, platforms, or solution level code to existing products. Basic Qualifications: Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 5 years of experience performing data analytics A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 3 years of experience performing data analytics A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) Preferred Qualifications: Master's Degree in "STEM" field (Science, Technology, Engineering, or Mathematics), or PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) Experience working with AWS At least 3 years' experience in Python, Scala, or R At least 3 years' experience with machine learning At least 3 years' experience with SQL 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: $158,600 - $181,000 for Princ Associate, Data Science New York, NY: $173,000 - $197,400 for Princ Associate, Data Science San Jose, CA: $173,000 - $197,400 for Princ Associate, Data Science Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Job DescriptionJob DescriptionAbout Pair Team Pair Team is building a new kind of healthcare system across Medicaid, Medicare, and public assistance programs: one that recognizes that access to housing, nutritious food, and reliable transportation are just as critical to health as having the right medications or seeing a doctor. As a public benefit corporation and AI-enabled medical group, we partner with shelters, food pantries, and community organizations to deliver "whole-person" care to the 115 million Americans who rely on the safety net. We are currently the largest complex care provider in California with over 500 employees and are expanding nationally. Our model replaces fragmented healthcare and social services systems with one trusted relationship for all medical, behavioral, and social needs. We improve access, build trust, and dramatically lower costs (52% fewer ER visits, 26% fewer hospitalizations). Our model is a rare combination of saving tax payer dollars ($150B annually at scale) while putting people on an upward life trajectory. At national scale, this approach would save taxpayers. These outcomes are driven by the AI-first, whole-person infrastructure we are building - a platform that connects healthcare and social-service organizations into a unified network. Leveraging our vast data and years of operational experience, we are building the agentic infrastructure for the safety net to coordinate care, automate operations, and learn from every patient interaction to continuously improve outcomes. Check out the AI-First Medicaid System we are building here. Forbes: For Pair Team, Accessibility Is About Delivering Healthcare To Those Who Need It The Most TechCrunch: Building for Medicaid's regulatory moment with Neil Batlivala from Pair Team Journal of General Internal Medicine: A Novel Intervention for Medicaid Beneficiaries with Complex Needs About the Role As a Staff AI Engineer, you will help design and build the architecture that enables this evolution, translating complex care processes into reliable, production-grade AI systems in close partnership with product and domain experts. What You'll Do Lead the design and evolution of agentic systems that participate directly in care delivery, helping coordinate care, engage patients, and execute meaningful portions of care workflows. Define and build architectural patterns for agent reasoning, tool use, memory, and human-in-the-loop collaboration. Develop both reusable platform capabilities and product-facing implementations, balancing long-term architecture with rapid iteration. Own complex problem spaces end-to-end - from system design and implementation through observability, evaluation, and continuous improvement in production. Partner closely with product managers, operators, and domain experts to translate complex real-world processes into reliable agent behavior. Establish standards and best practices for agent evaluation, safety, and operational reliability as these systems evolve toward greater autonomy Mentor engineers and influence technical direction across teams building agent-driven capabilities. Who You Are Systems-Oriented Technical Leader: You think in systems, not features. You make strong architectural decisions, navigate trade-offs effectively, and help shape technical direction across teams. Applied Agentic AI Builder: You've built production agentic AI systems that perform meaningful work. You understand agent behavior, tool orchestration, stateful workflows, and the realities of operating AI systems in production. Product-Minded Engineer: You work closely with product managers and domain experts to define problems and translate ambiguity into clear technical solutions. You care about outcomes, not just implementation. Strong Judgment in Ambiguity: You're comfortable operating in evolving problem spaces, balancing experimentation with reliability and knowing when to prioritize speed versus long-term investment. Data & Evaluation Driven: You use metrics, evaluation frameworks, and operational feedback to guide decisions and continuously improve system performance. Highly Autonomous Executor: You take ownership of complex problem spaces end-to-end, balancing speed with engineering rigor and iterating effectively based on real-world feedback. What You'll Need 6+ years of experience building and shipping production software systems, including experience operating at a Staff or Principal IC level and driving technical direction across complex systems Proven experience building and scaling multi-agent or agent-driven systems in production and real-world operational ownership (beyond simple chat or LLM workflows). Hands-on experience with modern agent ecosystems, including frameworks (e.g., LangGraph, Mastra, Claude Agents SDK), observability/evals tooling (e.g., Langfuse, LangSmith, Braintrust), MCP implementations, and leading AI SDKs (e.g., OpenAI, Anthropic). Strong systems and backend architecture fundamentals, with experience designing scalable, reliable systems and handling infrastructure, performance, failure modes, cost, and deployment concerns. Clear agentic evaluation mindset, including automated evals, simulation-based testing, regression frameworks, metrics design, and continuous improvement loops. Firsthand experience addressing performance and reliability of scaled agentic systems. AI-native builder with high velocity and ownership, demonstrating intellectual curiosity, rapid adoption of new tools, bias to action, and the ability to drive ambiguous problems from concept to production. Strong cross-functional collaborator and communicator, able to partner with Product, Operations, and domain experts to deliver end-to-end systems with measurable real-world impact. Force-multiplier technical leader, raising the bar for clarity of thinking, system design standards, and team execution. Nice to Have (Not Required) Experience building conversational or voice-driven systems (e.g., speech pipelines, telephony integrations, or real-time conversational workflows). Experience working in healthcare or other regulated or high-stakes domains. Our Values Lead with integrity: We keep our commitments and take responsibility for our actions. We are dependable and choose authenticity over perfection. Embrace challenges: We leave our egos at the door and step forward into discomfort instead of back into safety. We help each other to learn and provide feedback using candor and kindness. Break through walls: We go the extra mile for our patients, partners and one another, and we run toward hard things. We are resilient in our push for consistent improvement and challenge the status quo. Act beyond yourself: We build each other up and respect boundaries. We seek first to understand and assume positive intent. Care comes first: We hold ourselves to the highest standards for our patients. We are relentless in the pursuit of our mission, and ensure that we are taking care of ourselves in order to care for others. Because We Value You Competitive salary: $210,000 - 235,000 Equity compensation package Flexible vacation policy - take the time you need to recharge Comprehensive medical, dental, and vision coverage 401(k) 100% company-sponsored short and long-term disability and life insurance Subsidized backup childcare and caregiver supports through Wellthy Work entirely from the comfort of your own home Monthly $100 work from home expense stipend We provide the equipment needed for the role Opportunity for rapid career progression with plenty of room for personal growth! Travel reimbursements for any company retreats or leadership offsites Pair Team is an Equal Opportunity Employer. At Pair Team, we value diversity and strive to provide an inclusive environment for all applicants and employees. All applicants will be considered without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), national origin, marital status, age, disability, political affiliation, military service, genetic information, or any other characteristic covered by federal, state, or local law. Pair Team participates in E-Verify to verify employment eligibility for new hires. Any offer of employment at Pair Team is conditioned upon passing a pre-employment background check. Following a conditional job offer, candidates will undergo comprehensive employment background checks, including; criminal history, reference checks, and driving records if a role requires vehicle use. We do not conduct any TA business outside of emails. If you're ever concerned about spam or fraudulent activity, please reach out to . Note: Please be aware that while we sincerely appreciate your interest, due to the high volume of requests, we're unable to respond to general position inquiries via email. To apply for a position with us, please submit your application for the role you are interested in. Our team regularly reviews applications and will reach out to candidates whose qualifications align with our current openings listed below. Thank you!

Job DescriptionJob DescriptionAbout Pair Team Pair Team is building a new kind of healthcare system across Medicaid, Medicare, and public assistance programs: one that recognizes that access to housing, nutritious food, and reliable transportation are just as critical to health as having the right medications or seeing a doctor. As a public benefit corporation and AI-enabled medical group, we partner with shelters, food pantries, and community organizations to deliver "whole-person" care to the 115 million Americans who rely on the safety net. We are currently the largest complex care provider in California with over 500 employees and are expanding nationally. Our model replaces fragmented healthcare and social services systems with one trusted relationship for all medical, behavioral, and social needs. We improve access, build trust, and dramatically lower costs (52% fewer ER visits, 26% fewer hospitalizations). Our model is a rare combination of saving tax payer dollars ($150B annually at scale) while putting people on an upward life trajectory. At national scale, this approach would save taxpayers. These outcomes are driven by the AI-first, whole-person infrastructure we are building - a platform that connects healthcare and social-service organizations into a unified network. Leveraging our vast data and years of operational experience, we are building the agentic infrastructure for the safety net to coordinate care, automate operations, and learn from every patient interaction to continuously improve outcomes. Check out the AI-First Medicaid System we are building here. Forbes: For Pair Team, Accessibility Is About Delivering Healthcare To Those Who Need It The Most TechCrunch: Building for Medicaid's regulatory moment with Neil Batlivala from Pair Team Journal of General Internal Medicine: A Novel Intervention for Medicaid Beneficiaries with Complex Needs About the Role As a Staff AI Engineer, you will help design and build the architecture that enables this evolution, translating complex care processes into reliable, production-grade AI systems in close partnership with product and domain experts. What You'll Do Lead the design and evolution of agentic systems that participate directly in care delivery, helping coordinate care, engage patients, and execute meaningful portions of care workflows. Define and build architectural patterns for agent reasoning, tool use, memory, and human-in-the-loop collaboration. Develop both reusable platform capabilities and product-facing implementations, balancing long-term architecture with rapid iteration. Own complex problem spaces end-to-end - from system design and implementation through observability, evaluation, and continuous improvement in production. Partner closely with product managers, operators, and domain experts to translate complex real-world processes into reliable agent behavior. Establish standards and best practices for agent evaluation, safety, and operational reliability as these systems evolve toward greater autonomy Mentor engineers and influence technical direction across teams building agent-driven capabilities. Who You Are Systems-Oriented Technical Leader: You think in systems, not features. You make strong architectural decisions, navigate trade-offs effectively, and help shape technical direction across teams. Applied Agentic AI Builder: You've built production agentic AI systems that perform meaningful work. You understand agent behavior, tool orchestration, stateful workflows, and the realities of operating AI systems in production. Product-Minded Engineer: You work closely with product managers and domain experts to define problems and translate ambiguity into clear technical solutions. You care about outcomes, not just implementation. Strong Judgment in Ambiguity: You're comfortable operating in evolving problem spaces, balancing experimentation with reliability and knowing when to prioritize speed versus long-term investment. Data & Evaluation Driven: You use metrics, evaluation frameworks, and operational feedback to guide decisions and continuously improve system performance. Highly Autonomous Executor: You take ownership of complex problem spaces end-to-end, balancing speed with engineering rigor and iterating effectively based on real-world feedback. What You'll Need 6+ years of experience building and shipping production software systems, including experience operating at a Staff or Principal IC level and driving technical direction across complex systems Proven experience building and scaling multi-agent or agent-driven systems in production and real-world operational ownership (beyond simple chat or LLM workflows). Hands-on experience with modern agent ecosystems, including frameworks (e.g., LangGraph, Mastra, Claude Agents SDK), observability/evals tooling (e.g., Langfuse, LangSmith, Braintrust), MCP implementations, and leading AI SDKs (e.g., OpenAI, Anthropic). Strong systems and backend architecture fundamentals, with experience designing scalable, reliable systems and handling infrastructure, performance, failure modes, cost, and deployment concerns. Clear agentic evaluation mindset, including automated evals, simulation-based testing, regression frameworks, metrics design, and continuous improvement loops. Firsthand experience addressing performance and reliability of scaled agentic systems. AI-native builder with high velocity and ownership, demonstrating intellectual curiosity, rapid adoption of new tools, bias to action, and the ability to drive ambiguous problems from concept to production. Strong cross-functional collaborator and communicator, able to partner with Product, Operations, and domain experts to deliver end-to-end systems with measurable real-world impact. Force-multiplier technical leader, raising the bar for clarity of thinking, system design standards, and team execution. Nice to Have (Not Required) Experience building conversational or voice-driven systems (e.g., speech pipelines, telephony integrations, or real-time conversational workflows). Experience working in healthcare or other regulated or high-stakes domains. Our Values Lead with integrity: We keep our commitments and take responsibility for our actions. We are dependable and choose authenticity over perfection. Embrace challenges: We leave our egos at the door and step forward into discomfort instead of back into safety. We help each other to learn and provide feedback using candor and kindness. Break through walls: We go the extra mile for our patients, partners and one another, and we run toward hard things. We are resilient in our push for consistent improvement and challenge the status quo. Act beyond yourself: We build each other up and respect boundaries. We seek first to understand and assume positive intent. Care comes first: We hold ourselves to the highest standards for our patients. We are relentless in the pursuit of our mission, and ensure that we are taking care of ourselves in order to care for others. Because We Value You Competitive salary: $210,000 - 235,000 Equity compensation package Flexible vacation policy - take the time you need to recharge Comprehensive medical, dental, and vision coverage 401(k) 100% company-sponsored short and long-term disability and life insurance Subsidized backup childcare and caregiver supports through Wellthy Work entirely from the comfort of your own home Monthly $100 work from home expense stipend We provide the equipment needed for the role Opportunity for rapid career progression with plenty of room for personal growth! Travel reimbursements for any company retreats or leadership offsites Pair Team is an Equal Opportunity Employer. At Pair Team, we value diversity and strive to provide an inclusive environment for all applicants and employees. All applicants will be considered without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), national origin, marital status, age, disability, political affiliation, military service, genetic information, or any other characteristic covered by federal, state, or local law. Pair Team participates in E-Verify to verify employment eligibility for new hires. Any offer of employment at Pair Team is conditioned upon passing a pre-employment background check. Following a conditional job offer, candidates will undergo comprehensive employment background checks, including; criminal history, reference checks, and driving records if a role requires vehicle use. We do not conduct any TA business outside of emails. If you're ever concerned about spam or fraudulent activity, please reach out to . Note: Please be aware that while we sincerely appreciate your interest, due to the high volume of requests, we're unable to respond to general position inquiries via email. To apply for a position with us, please submit your application for the role you are interested in. Our team regularly reviews applications and will reach out to candidates whose qualifications align with our current openings listed below. Thank you!

Job DescriptionJob DescriptionAbout Pair Team Pair Team is building a new kind of healthcare system across Medicaid, Medicare, and public assistance programs: one that recognizes that access to housing, nutritious food, and reliable transportation are just as critical to health as having the right medications or seeing a doctor. As a public benefit corporation and AI-enabled medical group, we partner with shelters, food pantries, and community organizations to deliver "whole-person" care to the 115 million Americans who rely on the safety net. We are currently the largest complex care provider in California with over 500 employees and are expanding nationally. Our model replaces fragmented healthcare and social services systems with one trusted relationship for all medical, behavioral, and social needs. We improve access, build trust, and dramatically lower costs (52% fewer ER visits, 26% fewer hospitalizations). Our model is a rare combination of saving tax payer dollars ($150B annually at scale) while putting people on an upward life trajectory. At national scale, this approach would save taxpayers. These outcomes are driven by the AI-first, whole-person infrastructure we are building - a platform that connects healthcare and social-service organizations into a unified network. Leveraging our vast data and years of operational experience, we are building the agentic infrastructure for the safety net to coordinate care, automate operations, and learn from every patient interaction to continuously improve outcomes. Check out the AI-First Medicaid System we are building here. Forbes: For Pair Team, Accessibility Is About Delivering Healthcare To Those Who Need It The Most TechCrunch: Building for Medicaid's regulatory moment with Neil Batlivala from Pair Team Journal of General Internal Medicine: A Novel Intervention for Medicaid Beneficiaries with Complex Needs About the Role As a Staff AI Engineer, you will help design and build the architecture that enables this evolution, translating complex care processes into reliable, production-grade AI systems in close partnership with product and domain experts. What You'll Do Lead the design and evolution of agentic systems that participate directly in care delivery, helping coordinate care, engage patients, and execute meaningful portions of care workflows. Define and build architectural patterns for agent reasoning, tool use, memory, and human-in-the-loop collaboration. Develop both reusable platform capabilities and product-facing implementations, balancing long-term architecture with rapid iteration. Own complex problem spaces end-to-end - from system design and implementation through observability, evaluation, and continuous improvement in production. Partner closely with product managers, operators, and domain experts to translate complex real-world processes into reliable agent behavior. Establish standards and best practices for agent evaluation, safety, and operational reliability as these systems evolve toward greater autonomy Mentor engineers and influence technical direction across teams building agent-driven capabilities. Who You Are Systems-Oriented Technical Leader: You think in systems, not features. You make strong architectural decisions, navigate trade-offs effectively, and help shape technical direction across teams. Applied Agentic AI Builder: You've built production agentic AI systems that perform meaningful work. You understand agent behavior, tool orchestration, stateful workflows, and the realities of operating AI systems in production. Product-Minded Engineer: You work closely with product managers and domain experts to define problems and translate ambiguity into clear technical solutions. You care about outcomes, not just implementation. Strong Judgment in Ambiguity: You're comfortable operating in evolving problem spaces, balancing experimentation with reliability and knowing when to prioritize speed versus long-term investment. Data & Evaluation Driven: You use metrics, evaluation frameworks, and operational feedback to guide decisions and continuously improve system performance. Highly Autonomous Executor: You take ownership of complex problem spaces end-to-end, balancing speed with engineering rigor and iterating effectively based on real-world feedback. What You'll Need 6+ years of experience building and shipping production software systems, including experience operating at a Staff or Principal IC level and driving technical direction across complex systems Proven experience building and scaling multi-agent or agent-driven systems in production and real-world operational ownership (beyond simple chat or LLM workflows). Hands-on experience with modern agent ecosystems, including frameworks (e.g., LangGraph, Mastra, Claude Agents SDK), observability/evals tooling (e.g., Langfuse, LangSmith, Braintrust), MCP implementations, and leading AI SDKs (e.g., OpenAI, Anthropic). Strong systems and backend architecture fundamentals, with experience designing scalable, reliable systems and handling infrastructure, performance, failure modes, cost, and deployment concerns. Clear agentic evaluation mindset, including automated evals, simulation-based testing, regression frameworks, metrics design, and continuous improvement loops. Firsthand experience addressing performance and reliability of scaled agentic systems. AI-native builder with high velocity and ownership, demonstrating intellectual curiosity, rapid adoption of new tools, bias to action, and the ability to drive ambiguous problems from concept to production. Strong cross-functional collaborator and communicator, able to partner with Product, Operations, and domain experts to deliver end-to-end systems with measurable real-world impact. Force-multiplier technical leader, raising the bar for clarity of thinking, system design standards, and team execution. Nice to Have (Not Required) Experience building conversational or voice-driven systems (e.g., speech pipelines, telephony integrations, or real-time conversational workflows). Experience working in healthcare or other regulated or high-stakes domains. Our Values Lead with integrity: We keep our commitments and take responsibility for our actions. We are dependable and choose authenticity over perfection. Embrace challenges: We leave our egos at the door and step forward into discomfort instead of back into safety. We help each other to learn and provide feedback using candor and kindness. Break through walls: We go the extra mile for our patients, partners and one another, and we run toward hard things. We are resilient in our push for consistent improvement and challenge the status quo. Act beyond yourself: We build each other up and respect boundaries. We seek first to understand and assume positive intent. Care comes first: We hold ourselves to the highest standards for our patients. We are relentless in the pursuit of our mission, and ensure that we are taking care of ourselves in order to care for others. Because We Value You Competitive salary: $210,000 - 235,000 Equity compensation package Flexible vacation policy - take the time you need to recharge Comprehensive medical, dental, and vision coverage 401(k) 100% company-sponsored short and long-term disability and life insurance Subsidized backup childcare and caregiver supports through Wellthy Work entirely from the comfort of your own home Monthly $100 work from home expense stipend We provide the equipment needed for the role Opportunity for rapid career progression with plenty of room for personal growth! Travel reimbursements for any company retreats or leadership offsites Pair Team is an Equal Opportunity Employer. At Pair Team, we value diversity and strive to provide an inclusive environment for all applicants and employees. All applicants will be considered without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), national origin, marital status, age, disability, political affiliation, military service, genetic information, or any other characteristic covered by federal, state, or local law. Pair Team participates in E-Verify to verify employment eligibility for new hires. Any offer of employment at Pair Team is conditioned upon passing a pre-employment background check. Following a conditional job offer, candidates will undergo comprehensive employment background checks, including; criminal history, reference checks, and driving records if a role requires vehicle use. We do not conduct any TA business outside of emails. If you're ever concerned about spam or fraudulent activity, please reach out to . Note: Please be aware that while we sincerely appreciate your interest, due to the high volume of requests, we're unable to respond to general position inquiries via email. To apply for a position with us, please submit your application for the role you are interested in. Our team regularly reviews applications and will reach out to candidates whose qualifications align with our current openings listed below. Thank you!