Define the overall strategy and governance model for agent development, including frameworks, orchestration standards, evaluation protocols, and lifecycle management
Make key architectural decisions on orchestration frameworks (e.g., LangGraph, AutoGen), agent registries, and integration patterns, ensuring scalability and alignment with AI Acceleration priorities
Partner closely with Digital & Technology, engineering and products teams to maintain consistent architecture, shared infrastructure, and unified development standards
Oversee the design and rollout of core agent infrastructure, including evaluation systems, logging and observability platforms, and prompt repositories, in collaboration with cross-functional teams
Establish disciplined CI/CD and release management processes for agents, with clear versioning, rollback, and deployment controls
Ensure agent solutions integrate effectively with enterprise data systems, APIs, and security layers, aligned with information security and compliance standards
Define quality bars for agent performance, reliability, interpretability, latency, and safety, ensuring consistent evaluation across use cases
Implement automated testing and regression frameworks to maintain agent quality and compliance over time
Drive transparent reporting and performance reviews to demonstrate business impact and adherence to responsible AI principles
Build and lead a high-performing agent engineering function, fostering technical excellence, collaboration, and a culture of reusable blueprints and rapid iteration
Set strong technical direction, review design and architectural decisions, and mentor senior developers and leads to raise the overall engineering bar
Collaborate with data, product, and business teams to identify and scale high-value agent opportunities across commercial domains
Maintain close feedback loops between users and development teams to shape roadmaps based on adoption, performance, and impact
Communicate technical decisions and trade-offs clearly to senior stakeholders, connecting architectural choices to business outcomes
Requirements
15+ years’ experience in tech and/or analytics with a BA/BS
Prior experience leading large, matrixed global teams
Experience developing agentic AI systems, including orchestration, tool integration, and autonomous workflows using frameworks like LangChain, Semantic Kernel, AutoGen, Strands, CrewAI, and LangGraph.
Experience designing and implementing multi-agent systems, including task delegation, coordination, and autonomous decision-making
Certifications: Azure AI Engineer Associate, Azure Solutions Architect Expert; AWS Certified Machine Learning – Specialty, AWS Certified Solutions Architect – Professional; Professional Machine Learning Engineer, Professional Cloud Architect
Hands-on experience with LLMs, including prompt engineering, fine-tuning, and Retrieval-Augmented Generation (RAG) architecture
Expertise in MLOps / AIOps, covering monitoring, governance, lifecycle management, CI/CD pipelines, and cloud-native application development
Proficiency in API design, microservices architecture, and event-driven system development
Experience collaborating with offshore teams and distributed setups
Benefits
401(k) plan with Pfizer Matching Contributions
Additional Pfizer Retirement Savings Contribution
Paid vacation
Holiday and personal days
Paid caregiver/parental and medical leave
Health benefits including medical, prescription drug, dental, and vision coverage
Applicant Tracking System Keywords
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