Director, Build Engineer

ROLE SUMMARY This role owns hands-on software engineering delivery for the Medical Affairs AI Acceleration portfolio. This role turns solution architecture and product requirements into working, production-grade AI systems. This is a deeply technical, individual-contributor role. This position is accountable for designing components and writing, testing and shipping code to production. Decisions made in this role — how a feature is implemented, how AI-generated code is verified before it reaches production, how quickly a validated prototype is hardened into a scalable system — directly determine the reliability and velocity of the AI systems Medical Affairs depends on. This role carries individual technical authority over its assigned build area, reporting into the Senior Director, Engineering alongside two peer Build Engineers and the Data Integration Engineer. The role partners closely with Solution Architecture to implement architectural blueprints, with the Data Integration Engineer to incorporate data from various sources into the AI solutions, and with Product Management and UX/Experience Design to translate product and workflow requirements into working software solutions. Solutions will be deployed through the full life cycle including proofs of concepts, MVPs and production grade systems. The Director, Build Engineer is a hands-on software engineer who builds, tests, and ships the AI-powered products and platforms that make up the Medical Affairs AI Acceleration portfolio. Reporting to the Senior Director, Engineering, this role takes solution architecture and product requirements from prototype through production — writing full-stack code, integrating Agentic AI and LLM-based capabilities, and verifying AI-generated code with the same rigor applied to human-written code. This is an individual-contributor role built for engineers who move fluidly across the stack, work comfortably in ambiguity, and take personal ownership of whether what they ship actually works in production. ROLE RESPONSIBILITIES Full-Stack & AI System Build Build, test, and ship production-grade software across the stack, working in whatever language or framework the problem requires. Integrate Agentic AI, LLM-based capabilities, and RAG pipelines into Medical Affairs products, translating architectural design into deployed, functioning services. Take validated prototypes and MVPs through to production-grade systems, applying the quality gates and standards set by Solution Architecture and the Senior Director, Engineering. Write and maintain code that meets the team's engineering standards for quality, maintainability, and reuse. Document code, APIs, and system design decisions clearly and consistently as a standard part of the development process ensuring solutions are maintainable and understandable by others beyond the original author. AI-Augmented Development & Verification Use AI-augmented development tools to accelerate delivery, while applying rigorous verification and review to all AI-generated code before it ships. Apply LLM integration patterns (e.g., prompt design, multi-provider/model considerations, RAG) to build features that depend on generative AI capabilities. Monitor and troubleshoot AI/ML components in production, partnering with Solution Architecture on model performance, drift, and reliability issues. Design and optimize LLM and agent interactions for token efficiency — balancing prompt design, context window usage, and model selection to control cost and latency without sacrificing output quality. Data & Systems Integration Partner with the Data Integration Engineer to ensure builds are backed by reliable, well-governed data pipelines. Integrate with core enterprise systems (e.g., Veeva CRM, PromoMats, Salesforce Life Sciences/Marketing Cloud) as required by product and architecture specifications. Identify and resolve technical debt in owned build areas, balancing delivery speed against long-term system health. Cross-Functional Delivery Partnership Partner with Solution Architecture to implement architectural blueprints and flag design issues discovered during build. Partner with Product Management and UX/Experience Design to translate product and workflow requirements into working software, surfacing technical trade-offs early. Participate in sprint and iteration ceremonies with the Scrum Master, delivering committed work reliably. Continuous Improvement Maintain and grow deep, hands-on technical expertise across relevant languages, frameworks, and AI/ML tooling. Contribute to engineering documentation, code review practice, and knowledge-sharing that scales beyond the immediate build area. Bring emerging engineering and AI-development practices into the team's day-to-day work. BASIC QUALIFICATIONS Candidate demonstrates a breadth of diverse leadership experiences and capabilities including: the ability to influence and collaborate with peers, develop and coach others, oversee and guide the work of other colleagues to achieve meaningful outcomes and create business impact. Bachelor's degree in Computer Science, Engineering, or related field; 8+ years of hands-on software engineering experience. Demonstrated experience building and shipping production software across the full stack, with the ability to work across multiple languages and frameworks as needed. Experience integrating AI/ML or LLM-based capabilities into production systems. Experience taking prototypes/MVPs through to production-grade, scalable systems. Experience with modern cloud architecture (AWS or Azure), API-first design, and CI/CD practice. Experience with Agile/Scrum delivery frameworks. Strong verification and code-review discipline, including review of AI-generated code. Experience designing and optimizing LLM/agent prompts and workflows for token efficiency, balancing cost, latency, and output quality at production scale. Strong written communication skills, with a track record of producing clear, current technical documentation for code, APIs, and system design decisions. PREFERRED QUALIFICATIONS Experience in pharmaceutical, life sciences, or another regulated industry, with familiarity with GxP, HIPAA, and GDPR compliance requirements for engineered systems. Hands-on experience with LLMOps/MLOps tooling, vector databases, RAG pipeline engineering, or agent orchestration frameworks. Familiarity with Veeva CRM, Salesforce Life Sciences Cloud, or Salesforce Marketing Cloud integration patterns. Experience collaborating directly with business stakeholders to translate ambiguous problems into technical solutions. Relevant certifications (AWS/Azure Solutions Architect or Developer). Non-Standard Work Schedule, Travel, or Environment Requirements Must be able to travel to Pfizer offices, vendor offices, and other team meeting locations when required. Project work can sometimes be demanding and require work during off-hours to coordinate with global stakeholders or respond to production incidents. OTHER JOB DETAILS: Last Date to Apply for Job: October 01, 2026 Locations: