AI Engineer

• Lead the technical relationship for post-sale customers and act as their trusted advisor on deployment, adoption, and value realization
• Own account health, adoption velocity, and ongoing technical deployment and success across your portfolio
• Be an expert in all of OpenAI products across our API and agentic platform, Codex, ChatGPT Enterprise, and more and conduct technical enablement and configuration sessions across them
• Identify and validate use cases by embedding with customer teams to understand workflows and pain points
• Lead account level coordination across multiple workstreams, including new product activation, change management, and customer rollout and deployment planning
• Build strong relationships with executive sponsors and technical stakeholders and help align business goals with OpenAI capabilities
• Translate customer objectives into an actionable adoption roadmap with clear sequencing, milestones, and KPIs
• Partner with Solutions Architecture, Product, Engineering and Research by surfacing customer feedback, field patterns, and technical blockers and act as a cross functional navigator who keeps teams aligned, informed, and moving toward customer outcomes
• Guide value realization and measure impact through baselines, KPI definition, and post deployment reporting
• Facilitate workshops on use case design, adoption best practices, champion building, and internal enablement
• Help drive expansions by identifying high leverage opportunities where OpenAI’s platform can power new workflows or lines of business
• Serve as the technical advisor for existing customer implementations by guiding and optimizing account setup, configuration, etc.

AI Success Engineer – Healthcare, Life Sciences

• Build and ship Android features using Kotlin.
• Create clean mobile flows for insurance, payments, claims, renewals and financial services.
• Work with product and design to simplify complex user journeys.
• Integrate backend APIs and ensure mobile flows are stable, secure and reliable.
• Improve app performance, crash rate, loading states, responsiveness and memory usage.
• Use analytics, user behaviour and production issues to improve the product.
• Build AI-assisted mobile experiences only where they genuinely improve the user journey.

Mobile Application Developer – AI Finance Agent

• Build and ship native iOS features for onboarding, accounts, cards, payments, transfers, rewards and AI-assisted user journeys.
• Make complex financial flows feel clean, fast and simple on mobile.
• Work with product, design, backend and AI engineers to take ideas from rough concept to production release.
• Own app quality across performance, crash rate, loading states, edge cases, responsiveness and release stability.
• Use production feedback, analytics and customer behaviour to improve features after launch.
• Integrate APIs, authentication, secure data handling and financial workflows with strong attention to reliability.

iOS Developer – AI Finance Agent

• Design, build, and own the systems that power Voice AI and Text AI agents
• Craft system-level prompts that shape agent behavior and outcomes
• Develop tool-calling integrations for reliable real-world actions
• Build LLM-as-a-judge evaluations and AI observability
• Partner closely with product and design teams
• Apply industry-standard engineering practices
• Mentor and guide junior engineers

AI Engineer – AI Agents

• AI Implementation - Design, build, and maintain all of our AI systems across the company. Everything from internal marketing, sales, finance, and operations systems to local AI systems in our engineering workflows, and the Chamber itself.
• AI Adoption - Educate, Train, Support, and Uplift everyone in the company with their AI adoption. Running office hours, making tutorials, providing resources, sourcing solutions, and more.
• AI Infrastructure - Architect and operate a scalable set of infrastructure that allows non-technical, and technical teams to use AI in a secure and productive manner.
• AI Systems & Agents - In conjunction with departments, design, build and maintain all AI systems and agents. This includes administering and managing our off the shelf AI systems like Claude, Viktor, Cursor, etc. It also includes our custom built Agents, Skills, Plugins, Tools, and more.
• AI Security - You are responsible for creating, maintaining, and enforcing all data, privacy, and security policies across our AI systems and Agents. Organization, Department, and Role based permissions and settings across all our products.
• Other Projects - As this is a technical role, you will also be asked to help build other internal systems like automations, micro apps, and more.

AI Solutions Lead

• Build high-performance API services and implement complex RAG and Agentic AI architectures.
• Design and implement end-to-end RAG pipelines, including retrievers, vector stores (e.g., Pinecone, Weaviate, or pgvector), and generators.
• Optimize latency and relevance to ensure production-grade performance.
• Develop autonomous or semi-autonomous agents using frameworks such as LangChain, CrewAI, or Semantic Kernel.
• Manage orchestration, tool integration, and robust error handling for non-deterministic AI outputs.
• Assess performance, grounding accuracy, and hallucination detection using evaluation frameworks (e.g., RAGAS, TruLens).

Gen AI Engineer

• Define and maintain enterprise architecture standards, reference patterns, and governance guardrails for AI-enabled solutions moving from pilot to production.
• Establish decision models for build, buy, or integrate choices; model and vendor selection; data access; security; and responsible AI adoption.
• Design scalable architecture patterns for AI-enabled workflows and agentic processes across data, APIs, identity, security, and cloud platforms.
• Test new AI models, LLMs, agent frameworks, and tools to inform enterprise adoption.
• Design proof-of-concepts, define success criteria, and guide solutions from pilot to production.
• Lead architecture reviews and communicate trade-offs, risks, and growth to partners.
• Partner with teams to translate needs into governed, implementation-ready solutions.
• Ensure teams through demos, workshops, and reusable templates to support safe AI adoption.

Principal Architect – Enterprise AI

• Establishes the architectural patterns, evaluation practices, and deployment standards for the team
• Makes framework and model recommendations that set the foundation for the team
• Collaborates with the AI Enablement Manager and business unit to optimize operational processes, owning the infrastructure architecture and translating strategic direction into technical plans, product life cycles, a prioritized backlog, and buildable work
• Owns solutions end-to-end: technically planning, architecture, build, and deployment, then continuously monitors, iterates, and improves them to keep them reliable in production
• Partners with data governance to ensure solutions meet compliance, data quality, and operational standards
• Builds and continuously maintains the monitoring, evaluation, and regression detection systems that keep production agents reliable over time, including logging, performance benchmarking, and feedback loops that surface drift early.
• Leads the team as it grows, onboarding new team members like AI Product Manager and AI Operations Specialists for intake, sequencing, stakeholder coordination, and product ownership of deployed solutions.

Lead AI Engineer, Business Operations

• Direct AI enablement across CPX, transitioning from hands-on tactical execution to scalable, department-wide strategic leadership
• Own and maintain a comprehensive catalogue of AI use cases across CPX functions (Professional Services, Customer Success, Support), serving as the critical link to turn team ideas into standard operational workflows
• Define and continuously improve processes for the internal utilization of generative AI, autonomous agents, and machine-assisted development workflows
• Consult with CPX functions—including Professional Services, Customer Success, and Support—to identify, prioritize, and formalize intake workflows for a continuous pipeline of agentic solutions
• Partner directly with Business Technology and InfoSec to ensure secure-by-default practices, compliance, adoption, and lifecycle management of AI tooling
• Own responsibility for managing CPX AI technology spend, monitoring ROI, tracking financial benchmarks, and implementing measurement frameworks to quantify cost metrics against output volume
• Drive the definition of success in highly ambiguous spaces, utilizing a structured 30-60-90 day roadmap to establish empirical baselines, execute controlled pilots, and scale delivery
• Identify and document shadow or undocumented workflows across CPX functions to develop AI-augmented standards that drive successful sub-functional outcomes
• Provide mentorship, technical oversight, and strategic direction to distributed AI Champions and cross-functional project teams without formal administrative people management responsibilities
• Operate as an advanced individual contributor to standardize processes for enablement, deployment, tool assessment, and prototyping AI solutions

AI Operations Lead, CPX

• Build agentic workflows for decision-making in healthcare
• Design and ship AI systems for healthtech
• Raise the technical bar across the organization
• Support and close exceptional founders in health technology

Principal Applied AI Engineer

• Leads the evaluation, deployment, and governance of AI-powered tools and services within PCS, including Anthropic, and Copilot for M365; develops adoption frameworks, monitors usage, and ensures responsible AI use aligned with campus policy.
• Researches, consults, prototypes, and develops new and advanced standards-based technology initiatives and problem resolution across multiple systems
• Designs large components and/or coordinates the running, maintaining, and operating of technical systems and infrastructure
• Integrates, designs, reviews, troubleshoots, monitors, and resolves highly complex, strategically significant, and innovative enterprise-wide supported services, systems, networks, and application problems according to established processes and procedures
• Plans and directs staff implementation of complex enterprise technical projects
• Serves as the main expert point of contact with external stakeholders, leadership, vendors, peer institutions, and IT partners regarding high-level system integrations.
• Identifies needs, provides solution options and strategic direction, and communicates issue updates and resolutions

AI Technical Lead

• Define and Maintain the Wind Engineering AI Governance Framework
• Establish and Enforce Responsible AI Policies
• Oversee Risk Management, Validation, and Auditability
• Govern Cybersecurity, IP Protection, and Data Privacy for AI
• Provide Governance Approval and Oversight for AI Deployments
• Partner with Legal, Security, Privacy, and Compliance Teams

Governance & Responsible AI Leader

• Define product vision and prioritize initiatives across multiple applications
• Oversee requirements for gathering, feature design, and release planning
• Guide product owners and analysts to align deliverables with business outcomes
• Engage with stakeholders at all levels to champion product usability and value
• Coordinate with QA and development managers to ensure on-time delivery

Lead AI Engineer – Capital Project Delivery

• De sign, de velop, and fine-tune a variety of AI models
• Design autonomous agents and multi-step pipelines using LangChain, ReAct, tool-calling, or custom orchestration
• Build Retrieval-Augmented Generation pipelines that combine external knowledge bases with LLMs to improve factual accuracy for warfighting applications
• Implement end-to-end data pipelines, ETL processes, and back-end services (Python, C/C++, Java) that feed data to models
• Create CI/CD pipelines for model training, validation, containerized deployment (Docker/Kubernetes), and security scanning
• Maintain model registries, monitoring, and version control of context protocols
• Produce rapid prototypes, run benchmarks, and conduct robustness/adversarial testing in realistic environments
• Work closely with senior ML engineers, software developers, and government customers; mentor junior staff and contribute to design reviews and documentation
• Stay current with emerging LLM architectures, agentic paradigms, PEFT/LoRA methods, and AI-safety techniques; translate new research into operational capabilities

AI Engineer – Mission Innovation Lab

• Own the enterprise AI Governance architecture roadmap and technical implementation for OneTrust and associated GRC platforms.
• Define and lead enterprise architecture for AI Governance and Cyber GRC workflows.
• Own end-to-end AI governance lifecycle design: intake, classification, risk tiering, review/approval gates, exception handling, monitoring, and periodic reassessment.
• Translate policy and regulatory obligations into technical control patterns and reusable architecture blueprints deployable across UAT and production.
• Design and govern resilient API integrations across OneTrust, Archer, and broader enterprise systems.
• Establish role, group, and organizational segmentation architecture to enforce least-privilege access and scalable governance operations.
• Lead architecture decisions for automation, error handling, observability, incident response, and production support readiness.
• Chair cross-functional architecture reviews and influence risk, compliance, and engineering decision forums on control design and prioritization.
• Mentor engineers and analysts through architecture standards, implementation playbooks, and design quality reviews.

AI GRC Architect

• As a Senior AI Engineer within Bristol Myers Squibb's AI Venture Studio team, you will be a hands-on individual contributor responsible for building secure cloud-hosted applications.
• Design APIs, services, infrastructure patterns, deployment pipelines, and semantic-layer evolution patterns for agent context engineering.
• Collaborate with frontend engineers to define clean API contracts, streaming response patterns, error handling, and service-level behaviors for AI-powered user experiences.
• Create and maintain CI/CD pipelines, environment configuration, automated tests, and release processes for cloud AI applications.
• Partner with AI Engineers, Data Engineers, Data Scientists, and product teams to solve complex delivery challenges.
• Continuously refine delivery priorities and deliver MVP transition activities by maturing AI capabilities.

Senior AI Engineer

• Design, evolve, and own the enterprise AI governance framework, including use case intake workflows, risk classification standards, approval criteria, policy management, and responses to client RFP inquiries related to AI governance.
• Set the strategic direction for how governance scales with the organization’s growing AI footprint.
• Serve as the primary governance liaison to the Architecture Review Board, establishing review criteria for AI deployments and ensuring governance checkpoints are embedded in the release management lifecycle.
• Partner with Compliance to design and maintain the AI compliance monitoring approach, defining what gets monitored, how exceptions are surfaced, and how remediation is tracked.
• Proactively identify emerging risk patterns and recommend policy adjustments.
• Lead the organization’s response to evolving AI legislation and healthcare specific regulatory requirements by partnering with Legal, translating legal and regulatory developments into operational policies, stakeholder communications, and process updates that keep the organization ahead of compliance obligations.
• Own the enterprise AI use case inventory, including its structure, taxonomy, and lifecycle stages.
• Ensure every use case is accurately classified, tracked through approval, and documented with risk disposition and ownership.
• Define and continuously improve the AI risk assessment methodology, including scoring criteria, workflow design, and integration with the organization’s GRC platform (LogicGate).
• Collaborate with Vendor Management to establish the vendor AI evaluation framework, assessing model documentation for fairness, bias, transparency, and performance claims.
• Design and deliver the quarterly AI governance reporting package, including use case dashboards, risk trend analysis, and executive summaries.
• Present findings and recommendations to leadership, drive accountability for follow through on identified priorities, and use reporting insights to inform program strategy.
• Facilitate AI governance committee meetings and cross functional workgroups, setting agendas, framing decisions, facilitating productive discussion, and documenting outcomes.
• Manage escalation paths across governance tiers and represents the AI governance program in leadership forums and senior stakeholder meetings.
• Collaborate with Learning Services on the enterprise AI adoption and enablement strategy, including training roadmaps, engagement campaigns, usage analytics, and feedback loops.
• Drive measurable adoption outcomes and continuously refine the approach based on user behavior and organizational readiness.
• Collaborate and partner with engineering on proof of concept AI initiatives, including conversational agents and workflow automations, from problem framing through pilot evaluation.
• Other duties as assigned.

Lead, AI Governance – Enablement

• Leading cloud VM platform initiatives from architecture and systems design through implementation, testing, and deployment.
• Designing, building, and operating scalable services that support secure, isolated agent workloads.
• Developing automation for infrastructure provisioning, VM lifecycle management, application delivery, configuration, monitoring, and remediation.
• Collaborating with engineering teams across NVIDIA to translate business and AI workflow requirements into dependable platform capabilities.
• Improving the platform’s reliability, scalability, observability, performance, and operational efficiency.
• Continuously raising standards for code quality, testing, documentation, infrastructure security, and production readiness.

Senior Software Engineer, AI Agent Compute

• Define and evolve the standards, architecture patterns, and tooling choices that govern how engineers use AI across the codebase — including where to invest in codebase readiness (instrumentation, specification, evaluation) versus targeted rewrites.
• Own execution of the multi-milestone plan (readiness → validated → governed) applied to corgi and secondary repos, in partnership with squad leads — without being their manager.
• Decide what AI tooling, agent infrastructure, and evaluation pipelines the org needs, and build or oversee the build of the ones that don't exist yet.
• Set the policy and technical controls for where human-in-the-loop review is required versus where autonomous agent action (PR review, deployment) is safe — resolving the tension between adoption speed and security/quality risk.
• Write the guidance engineers actually use — AGENTS.md/CLAUDE.md conventions, review norms for AI-generated code, eval standards — and make sure it's adopted, not just published.

AI Engineer jobs in United States

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AI Success Engineer – Healthcare, Life Sciences

Mobile Application Developer – AI Finance Agent

iOS Developer – AI Finance Agent

AI Engineer – AI Agents

AI Solutions Lead

Gen AI Engineer

Principal Architect – Enterprise AI

Lead AI Engineer, Business Operations

AI Operations Lead, CPX

Principal Applied AI Engineer

AI Technical Lead

Governance & Responsible AI Leader

Governance & Responsible AI Leader

Lead AI Engineer – Capital Project Delivery

AI Engineer – Mission Innovation Lab

AI GRC Architect

Senior AI Engineer

Lead, AI Governance – Enablement

Senior Software Engineer, AI Agent Compute

AI Architect