Applied AI Engineer, Enterprise - Healthcare Life Sciences (HLS)

Details

Across industries, the Applied AI Engineering team helps organizations turn frontier AI into safe, reliable production systems that deliver meaningful business outcomes. The team works directly with customers’ engineering, product, security, and transformation teams to navigate complex architectures, data environments, governance requirements, and organization-wide change.

As an Enterprise Applied AI Engineer, you will serve as a technical partner to organizations in the Healthcare and Life Sciences segment. You will help turn ambitious AI use cases into durable production systems and drive adoption at scale through hands-on engineering and technical leadership. The role includes writing and debugging code, building evaluation systems, resolving complex integrations, and guiding decisions involving model behavior, reliability, latency, cost, safety, security, governance, and operational readiness.

The role may be based in New York City or San Francisco, or performed remotely. Office-based employees follow a hybrid work model with three days per week in the office.

Responsibilities

• Design, build, evaluate, and deploy AI systems from prototype through reliable production and scaled adoption.
• Partner with enterprise customers to identify high-value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and success criteria.
• Make technical decisions across model selection, agent and tool design, retrieval, context design, data pipelines, evaluation, reliability, observability, latency, cost, safety, security, and governance.
• Diagnose complex implementation challenges, reproduce failures, test hypotheses, and drive blockers to resolution.
• Collaborate with customer engineering teams and OpenAI Product, Research, Engineering, Security, and Go-to-Market teams to turn deployment experience into product feedback.
• Partner with customer security, privacy, clinical, and business teams to design responsible AI deployments, including data handling, access controls, evaluation, human oversight, and monitoring.
• Create reusable architectures, tooling, playbooks, and technical guidance for future enterprise deployments.

Requirements

• Experience designing, building, and shipping AI or machine-learning systems in enterprise environments, from prototype to production.
• Strong contributions through coding, architecture, evaluation, debugging, or production engineering. Relevant backgrounds may include applied AI or ML engineering, forward-deployed engineering, software engineering, customer engineering, solutions architecture, or technical consulting.
• High proficiency in Python and familiarity with model APIs, agent and tool development, retrieval and data pipelines, evaluation, observability, integrations, and production operations.
• Experience with JavaScript, TypeScript, or another relevant language is valuable.
• Ability to evaluate AI systems systematically using representative data, automated graders, production signals, and human judgment.
• Experience with enterprise production requirements, including integrations, reliability, observability, security, privacy, data governance, performance, and cost.
• Experience delivering AI or software in healthcare, life sciences, or similarly complex regulated enterprises, with measurable outcomes beyond a proof of concept.
• Familiarity with sensitive data, legacy systems, and interoperability.
• Ability to connect technical decisions to customer workflows, adoption, and measurable business outcomes.
• Clear and credible communication with engineers, technical leaders, security and product teams, and executives.
• Strong end-to-end ownership, technical judgment, and ability to work through ambiguity.
• Healthcare or life sciences experience is strongly preferred; candidates from other regulated enterprise environments are also encouraged to apply.
• Ability to learn quickly, challenge assumptions constructively, and collaborate with humility.

Benefits

• Base salary of $251,000–$278,000 per year.
• Equity and performance-related bonuses for eligible employees.
• Medical, dental, and vision insurance, with employer contributions to Health Savings Accounts.
• Pre-tax Flexible Spending Accounts and commuter benefits.
• 401(k) retirement plan with employer match.
• Paid parental, medical, and caregiver leave.
• Paid time off, company holidays, office closures, and paid sick or safe time.
• Mental health and wellness support.
• Employer-paid basic life and disability coverage.
• Annual learning and development stipend.
• Daily office meals and eligible meal delivery credits.
• Relocation support for eligible employees.
• Additional benefits may include charitable donation matching and wellness stipends.