PharmSci Agentic and Generative AI Architect
Pfizer
8 days ago
Remote friendly (San Diego, CA)
United States
IT
ROLE SUMMARY
Hands-on technical leader designing, building, and scaling agentic and generative AI solutions for Pharmaceutical Sciences initiatives; translating ideas into production-ready AI systems with strong engineering discipline, scalable architecture, and responsible AI.
ROLE RESPONSIBILITIES
- Design and implement agentic AI systems for multi-step reasoning, tool use, and autonomous task execution.
- Architect enterprise-grade GenAI solutions, including RAG pipelines, embedding strategies, orchestration layers, and evaluation frameworks.
- Lead PoCs and pilots and scale successful solutions into production-ready capabilities.
- Establish reusable architectural patterns, reference implementations, and technical standards for GenAI and agentic systems.
- Ensure reliability, observability, performance, and cost effectiveness.
- Integrate AI solutions with existing platforms, data sources, and workflows.
- Partner with science and product leads to translate requirements into technical designs and delivery milestones.
- Mentor developers and raise GenAI/agentic maturity.
- Embed governance, security, evaluation, and monitoring into design and deployment.
- Support sustainable operation through lifecycle and maintenance practices.
BASIC QUALIFICATIONS
- Degree in CS/Software Engineering/AI-ML or equivalent; 6+ years (Bachelor’s), 5+ (Master’s), or 1+ (PhD) relevant experience.
- Significant hands-on experience building production software and applied AI systems.
- Deep experience with GenAI, RAG architectures, and agentic workflow design.
- Strong programming skills (e.g., Python) and modern AI engineering practices.
PREFERRED QUALIFICATIONS
- Experience in regulated/process-heavy environments.
- Track record delivering reusable platforms/accelerators/reference architectures.
- Ability to communicate complex technical concepts to non-technical partners.
Application instructions
- Last date to apply: June 12, 2026.
- Hybrid role (live within commuting distance; ~2.5 days/week on-site).
Hands-on technical leader designing, building, and scaling agentic and generative AI solutions for Pharmaceutical Sciences initiatives; translating ideas into production-ready AI systems with strong engineering discipline, scalable architecture, and responsible AI.
ROLE RESPONSIBILITIES
- Design and implement agentic AI systems for multi-step reasoning, tool use, and autonomous task execution.
- Architect enterprise-grade GenAI solutions, including RAG pipelines, embedding strategies, orchestration layers, and evaluation frameworks.
- Lead PoCs and pilots and scale successful solutions into production-ready capabilities.
- Establish reusable architectural patterns, reference implementations, and technical standards for GenAI and agentic systems.
- Ensure reliability, observability, performance, and cost effectiveness.
- Integrate AI solutions with existing platforms, data sources, and workflows.
- Partner with science and product leads to translate requirements into technical designs and delivery milestones.
- Mentor developers and raise GenAI/agentic maturity.
- Embed governance, security, evaluation, and monitoring into design and deployment.
- Support sustainable operation through lifecycle and maintenance practices.
BASIC QUALIFICATIONS
- Degree in CS/Software Engineering/AI-ML or equivalent; 6+ years (Bachelor’s), 5+ (Master’s), or 1+ (PhD) relevant experience.
- Significant hands-on experience building production software and applied AI systems.
- Deep experience with GenAI, RAG architectures, and agentic workflow design.
- Strong programming skills (e.g., Python) and modern AI engineering practices.
PREFERRED QUALIFICATIONS
- Experience in regulated/process-heavy environments.
- Track record delivering reusable platforms/accelerators/reference architectures.
- Ability to communicate complex technical concepts to non-technical partners.
Application instructions
- Last date to apply: June 12, 2026.
- Hybrid role (live within commuting distance; ~2.5 days/week on-site).