Overview In this role you will own hands-on delivery of AI-powered software for the Medical Affairs AI Acceleration portfolio. You design, build, test, and ship production-grade systems, translating architecture and product requirements into reliable solutions. You work across data integration, solution architecture, product management, and UX to move prototypes from MVP to production. Your work directly impacts the reliability and velocity of AI systems used in Medical Affairs. You will operate in a fast-paced, technically deep environment with broad ownership.
Compensation / Benefits- 401(k) with Pfizer Matching Contributions
- Pfizer Retirement Savings Contribution
- paid vacation
- holiday and personal days
- paid caregiver/parental and medical leave
- health benefits (medical, prescription, dental, vision)
Responsibilities- Build, test, and ship production-grade software across the full stack in appropriate languages/frameworks
- Integrate Agentic AI, LLM-based capabilities, and RAG pipelines into products
- Advance validated prototypes/MVPs to production-grade systems following defined quality gates
- Write maintainable, well-documented code and APIs; document system design decisions
- Use AI-augmented development tools with rigorous verification of AI-generated code before production
- Design and optimize LLM/agent interactions for token efficiency and cost control
- Collaborate with Data Integration Engineer to ensure reliable data pipelines
- Integrate with core enterprise systems (Veeva CRM, PromoMats, Salesforce Life Sciences/Marketing Cloud) as needed
- Identify and resolve technical debt balancing speed and long-term health
- Partner with Solution Architecture, Product Management and UX to surface trade-offs early
- Participate in sprint ceremonies and deliver committed work reliably
- Maintain deep technical expertise and contribute to scalable engineering docs and practices
- Introduce emerging engineering and AI development practices into the team's daily work
Key requirements- 8+ years of hands-on software engineering experience
- Experience building and shipping production software across the full stack
- Experience integrating AI/ML or LLM-based capabilities into production systems
- Experience bringing prototypes/MVPs to production-grade, scalable systems
- Experience with modern cloud architecture (AWS or Azure), API-first design, and CI/CD
- Experience with Agile/Scrum delivery
- Strong verification and code-review discipline for AI-generated code
- Experience designing and optimizing LLM/agent prompts and workflows for production scale
- Strong written communication skills for technical documentation
- ability to influence and collaborate with peers
- coaching and mentoring others
- clear written communication
- Agentic AI integration
- LLM-based capabilities
- RAG pipelines
