At Pfizer, the impact of technology resonates through every facet of our operations, driving a transformative digital and 'data first' approach. Across all functions—from groundbreaking research to efficient manufacturing—we embrace innovative solutions that empower us to enhance every aspect of drug discovery and development. Your efforts in building robust, reusable AI Solutions and empowering development teams streamline processes, making our work not only faster but easier. In doing so, you contribute significantly to a mission that transcends mere efficiency; you become a vital part of saving countless lives.

As a Staff AI Engineer, you will be part of the AI Engineering Excellence team, responsible for defining, implementing, and enforcing enterprise-grade engineering standards for Applied AI solutions. You will work across AI Engineering teams to design reference architectures, validate solution feasibility, and ensure that AI systems are scalable, maintainable, observable, and compliant. You will act as a technical authority across the AI lifecycle—from design reviews and proof points to production readiness and hand-off.

You will report into the AI Engineering Excellence Lead and operate as a multiplier across the Applied AI Engineering organization. This role blends deep technical expertise, product engineering strategy, and direct enablement of enterprise use cases. You will partner closely with business and technical stakeholders to design and deliver robust, scalable solutions that demonstrate the value of AI across our enterprise. This role is execution-oriented with strong influence on the AI solution lifecycle—from ideation to hand-off.

description

Leadership & Oversight

• Serve as a technical authority for Applied AI Engineering, setting patterns and reference architectures for enterprise AI solutions.
• Design and review AI system architectures covering model lifecycle, inference patterns, data flows, evaluation, observability, and operational resilience.
• Lead deep technical reviews for complex or high-risk AI use cases, providing clear recommendations and trade-offs.

Engineering Standards & Quality

• Define and enforce engineering standards for AI solutions, including code quality, testing, performance, security, and deployment readiness.
• Contribute to and evolve the AI Engineering playbook, reusable frameworks, and shared libraries.
• Ensure solutions meet enterprise expectations for maintainability, scalability, and compliance.

Lifecycle & Delivery Enablement

• Partner with solution teams to translate business requirements into concrete technical designs aligned with platform and enterprise architecture constraints.
• Support smooth handoffs across the AI lifecycle—from exploration to build to production—by validating readiness and identifying gaps early.
• Actively unblock teams by providing hands-on technical guidance when needed.

Community & Enablement

• Play a leading role in the AI Engineering Community of Practice, sharing best practices, lessons learned, and emerging patterns.
• Mentor mid-level and junior engineers across teams, raising the overall technical bar.
• Contribute to technical documentation, solution diagrams, and internal training materials.

BASIC QUALIFICATIONS

• Advanced degree in Computer Science, Engineering or related discipline.
• 7+ years software engineering, ML engineering or Applied AI roles, with demonstrable experience building production AI systems.
• Strong system design skills across distributed systems, APIs, data pipelines, and AI/ML workflows.
• Hands-on experience with modern AI stacks (e.g., LLMs, retrieval systems, evaluation frameworks, MLOps patterns).
• Proven ability to operate as a senior IC influencing architecture and standards across multiple teams.
• Strong written and verbal communication skills, with the ability to explain complex technical concepts to technical and non-technical stakeholders.