Director, Applied AI

ROLE SUMMARY

As Director, Applied AI, you lead the realization of AI strategy into tangible, production-grade solutions, platforms, and products. You operate at the intersection of architecture, engineering, and product thinking — translating strategy, patterns, and standards into working systems deployed in real enterprise environments.

You own the end-to-end technical integrity of solutions — from concept through implementation — ensuring they are robust, scalable, and aligned with enterprise architecture and platform capabilities. You connect that build to business outcomes: you understand the commercial problem your work serves, not only the code. And you lead the people who build with you — full-time engineers, contractors, and vendor resources whose day-to-day execution you direct and whose work you review to Pfizer’s quality and security bar.

Why This Role Matters

Pfizer’s purpose — breakthroughs that change patients’ lives — has always depended on the company’s willingness to transform how it works, not only what it discovers. Being the most AI-forward company, and reinventing how we work from end to end, is the next chapter in that story. That depends on turning strategy into systems that actually work. This role ensures strategy and architecture become real, working solutions — deployable, integrated, and sustainable in production — and that the team and partners around you deliver to the same standard.

Candidate Profile

You are a hands-on technical leader with strong execution capability and architectural judgment. You operate across disciplines — architecture, engineering, and product — and drive solutions from ambiguous beginnings to production reality. You are known for enforcing technical truth: ensuring what is built is correct, complete, scalable, and aligned with enterprise systems. You can frame a technical decision in terms of the business outcome it serves, and you can lead a mixed team of engineers, contractors, and vendors to ship it.

ROLE RESPONSIBILITIES

1)  Solution & Platform Realization  — Translate strategic intent and architectural patterns into working AI solutions and platforms. Own the end-to-end architecture and implementation shape of major solutions, ensuring they are production-ready, scalable, maintainable, and aligned with enterprise architecture.

2)  Technical Leadership & Hands-on Execution  — Lead technical design and execution across complex initiatives as architect, tech lead, and delivery driver. Contribute hands-on code where it accelerates delivery and de-risks execution, and guide teams through design decisions, implementation trade-offs, and integration challenges.

3)  Integration Ownership  — Ensure seamless integration across platforms and services, data systems, AI models, and business workflows — connecting models to real use cases, guardrails to runtime systems, and observability to operational feedback loops within enterprise constraints.

4)  Team & Vendor Leadership  — Lead and coordinate a delivery team of full-time engineers, contractors, and vendor resources. Direct day-to-day technical execution, review their work to Pfizer’s quality and security bar, manage dependencies and throughput, and grow the capability of the people you lead.

5)  Technical Quality & Truth Enforcement  — Identify and challenge incomplete or fragile architectures, solutions that are not production-ready, and unrealistic assumptions. Enforce engineering discipline in scalability, observability, performance, and security so solutions meet enterprise quality and reliability standards.

6)  Business & Domain Translation  — Translate business problems into feasible, high-impact technical solutions, and communicate solution direction in terms of business and commercial outcomes. Provide grounded technical input into domain-level AI strategy.

QUALIFICATIONS

Basic Qualifications

• Bachelor’s degree required, advanced degree preferred.
• 10+ years or equivalent experience in software engineering, AI/ML, or architecture roles, with a strong delivery track record.
• Proven experience building production-grade AI/ML systems or platforms.
• Current hands-on coding ability and strong depth across at least 2–3 of: AI/ML and generative AI; system design / architecture; data engineering; cloud engineering.
• Demonstrated ability to lead complex technical initiatives end-to-end.
• Experience leading or coordinating engineers, contractors,…