Lead agentic engineering adoption, technical leadership, reusable engineering capabilities, and continuous improvement of AI-assisted software development practices.
Compensation
The estimated base salary range for this position is $157,400 to $216,400 at the time of posting. Actual compensation will be provided in writing at the time of offer, if applicable, and is based on several factors we believe fairly and accurately impact compensation, including geographic location, experience, knowledge, skills, abilities, and other job permitted factors. This position is eligible for a variable annual bonus, which is dependent upon achievement of your individual objectives and Company performance.
Responsibilities
Lead Agentic Engineering Adoption
Provide Technical Leadership
Develop Reusable Engineering Capabilities
Advance Agentic Engineering Practices
Mentor and Enable Engineering Teams
Requirements
Bachelor's degree in Computer Science, Software Engineering, or a related technical field. A master’s degree is a plus.
Nice to have: Experience in clinical diagnostics, medical devices, healthcare, or life sciences
Nice to have: Experience developing or maintaining AI-enabled software products subject to regulatory, quality, cybersecurity, or safety requirements
Nice to have: Experience applying AI and agentic workflows to requirements engineering, software architecture, code generation, automated testing, documentation, or software maintenance
Nice to have: Experience with AI agent frameworks, model APIs, retrieval-augmented generation (RAG), vector databases, or Model Context Protocol (MCP)
Lead Anthropic’s technology partnership strategy, build and scale joint businesses, and drive high‑stakes strategic partnerships with enterprise software and AI companies.
Locations (3)
San Francisco, California, United States
New York City, New York, United States
Seattle, Washington, United States
Compensation
Annual Salary: $365,000—$425,000 USD
Responsibilities
Set Anthropic's technology partner strategy
Hold executive relationships with strategic partners
Define the "better together" story with partners
Create repeatable co‑build, co‑sell, co‑market, and marketplace motions
Shape partnership structures with Business Development and account teams
Requirements
Lead Forward Deployed Engineer (FDE) - AI Platforms (ML, LLMs, APIs, ML Ops)
Lead Forward Deployed Engineer to accelerate Target's enterprise AI platform adoption, combining solution architecture, hands‑on engineering, and technical guidance.
Compensation
The pay range is $132,000.00 - $238,000.00
Responsibilities
Lead complex technical engagements that accelerate enterprise AI platform adoption
Design, build, and productionize AI solutions, reference implementations, technical tooling, and platform‑support capabilities
Guide technical design and implementation across engineering efforts
Apply software engineering and distributed systems expertise to improve reliability, security, performance, observability, and ops readiness
As an Enterprise AIE, you will serve as a technical partner to leading organizations within the Healthcare and Life Sciences segment (HLS), helping them turn ambitious AI use cases into durable production systems and adoption at scale.
Locations (2)
San Francisco, California, United States
New York City, New York, United States
Responsibilities
Work hands‑on in code to design, build, evaluate, and deploy AI systems from prototype to reliable production and scaled adoption that solve important customer problems and deliver measurable business outcomes.
Partner with enterprise customers to identify high‑value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and success criteria.
Make sound 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.
Lead the architecture and implementation of user-facing parts of Paystand’s systems, design and develop reusable libraries and frameworks, provide technical leadership and mentorship, and collaborate with product owners, designers, and other engineers to build the best user experience.
Responsibilities
Lead the architecture and implementation of user-facing parts of Paystand’s systems
Design and develop reusable libraries and frameworks that support complex web applications
Provide technical leadership and mentorship to other engineers
Collaborate with product owners, designers, and other engineers to build the best user experience
Ensure best practices in code quality, security, and performance
Lead the design, development, and delivery of AI platform capabilities that enable intelligent products and agentic experiences across B&MI. This role combines people leadership, technical ownership, and cross-functional delivery accountability.
Compensation
$140,000 - $231,000 USD
Responsibilities
Lead, coach, and develop one or more teams of software engineers by setting clear goals, managing performance, and creating development plans aligned to individual and organizational objectives.
Build a strong engineering culture focused on ownership, quality, accountability, and continuous improvement, and partner with leadership on hiring, team composition, and long-term planning.
Guide teams through change and ambiguity, connecting team priorities to broader business and enterprise goals.
Own end-to-end delivery of complex initiatives across multiple systems, services, or teams. This includes defining roadmaps and priorities with Product and stakeholders, managing dependencies and risks, and resolving cross-team blockers.
Establish execution frameworks for planning, estimation, and tracking that enable predictable, high-quality delivery.
Requirements
Bachelor's degree in Computer Science
Engineering
Nice to have: building reusable platform capabilities
Partner closely with customers’ engineering teams and OpenAI’s Product, Research, Engineering, Security, and Go‑to‑Market teams to turn deployment experience into actionable product feedback.
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