Executive Director, Head of Agentic Factory - Remote

Job Description Summary
This position can be based remotely anywhere in the U.S. (there may be some restrictions based on legal entity). Please note that this role would not provide relocation as a result. The expectation of working hours and travel (domestic and/or international) will be defined by the Hiring Manager. This position may require 10% plus travel. Job Description

The Executive Director, Head of Agentic Factory will lead the Agentic Factory responsible for designing, building, deploying, and scaling AI agents and autonomous workflows that transform commercial operations. This role combines AI engineering, product delivery, and platform leadership toestablishreusable agentic capabilities, accelerate innovation, and ensure secure, governed, and measurable business impact across the enterprise.

Major Accountabilities

- Lead the vision, strategy, and execution of the enterprise Agentic Factory.

- Build and scale reusable AI agents, orchestration frameworks, and agent development standards.

- Partner with product, engineering, and business leaders toidentifyand deliver high-value agentic AI use cases.

- Establishengineering best practices for LLMs, agent orchestration, evaluation, observability, security, and governance.

- Drive adoption of reusable tools, accelerators, and reference architectures that reduce time-to-value.

- Lead and develop a high-performing team of AI engineers, platform engineers, and solution architects.

- Measure and continuously improve the performance, reliability, and business value of deployed AI agents.

Education:

Bachelor's or advanced degree in Computer Science, Engineering, Artificial Intelligence, ora relatedfield.

Required experience and skill set:

- 12+ years of progressive experience leading AI engineering, platform engineering, software engineering, or enterprise technology organizations, including 5+ years leading managers or multidisciplinary technical teams.

- Experience scaling AI or data platforms in pharmaceutical, healthcare, life sciences, financial services, oranotherregulated enterprise.

- Proven record scaling generative AI, agentic AI, ML, automation, or platform products from experimentation to production with measurable adoption, reliability, and business value.

- Strong technical fluency across LLMs, multi-agent orchestration, RAG, vector/graph databases, APIs, cloud platforms,MLOps/LLMOps,DevSecOps, observability, evaluation, access controls, and enterprise integration patterns.

- Demonstratedability to build reusable engineering standards, reference architectures, accelerators, and developer enablement models that reduce duplication and improve speed-to-value.

- Experience managing portfolio prioritization, operating rhythms, technical debt, budget/resource trade-offs, vendor/partner orchestration, and risk governance for enterprise AI capabilities.

- Executive-level communication and influence, with ability to align Product, Engineering, Architecture, DDIT, security, legal/privacy, compliance, and business leaders around AI factory strategy and delivery.

Preferred experience and skill set:

- Experience with commercial operations, customer engagement, omnichannel, field enablement, content, analytics, or other high-value commercial use cases.

- Familiarity with Microsoft Azure AI Foundry/OpenAI, Semantic Kernel, Copilot Studio,LangChain/LangGraph, MCP/A2A, telemetry, prompt/model security testing, and AI ROI measurement.

- Track record attracting, developing, andretainingscarce AI engineering, architecture, product, and platform talent.

- Delivery of agreed product, platform, program, strategy, AI, or knowledge-engineering milestones within planned timelines.

- Stakeholder satisfaction, user adoption, business outcomes, and measurable value realization for assigned capabilities.

- Quality and completeness of strategy, roadmap, governance, delivery, technical, and executive reporting artifacts.

- Alignment with enterprise architecture, R