director, product engineering

The Director, Product Engineering will lead a global team of highly skilled software engineers responsible for designing, developing and sustaining enterprise-grade digital manufacturing applications and solutions. This leader will ensure engineering excellence across multiple complex and competing priorities balancing rapid delivery with stability, scalability and maintainability. 

This role requires a seasoned technical leader who can drive architectural vision, establish best practices and standards, mentor emerging engineering talent, and guide the adoption of modern technologies including AI and emerging Agentic AI paradigms. The ideal candidate combines deep software engineering expertise with strong leadership, prioritization, and a passion for enabling innovation within a complex, global organization.

ROLE RESPONSIBILITIES 

The Director, Product Engineering  colleague’s responsibilities include but are not limited to:

• Product Delivery & Execution Excellence

  • Oversee multiple concurrent development initatives supporting the Digital Manufacturing portfolio

  • Drive end-to-end solution delivery, architecture, design, development testing, deployment and sustainment

  • Manage competing priorities and resource allocations across projects, balancing delivery speed with quality and compliance

  • Partner with product managers, solution architects, and business stakeholders to align engineering coutcomes with product roadmaps

• Technical Architecture & Best Practices

  • Define and uphold modern engineering standards such as CI/CD pipelines, code reviews, automated testing, observability and secure-by-design principles

  • Ensure system architectures are scalable, reliable, and maintanable across global deployments

  • Manage technical debt and implement continuous improvement initiatives to enhance performance and efficiency

  • Drive alignment with enterprise architecture, data, and cybersecurity standards

• AI Enablement & Technology Integration

  • Partner with AI COE, Manufacturing Intelligence, Data Engineering and Platform Engineering teams to enable AI-powered features and intelligent automation

  • Maintain a high-level understanding of the tools, frameworks, and infrastructure supporting AI and agentic systems (e.g. LLMs, RAG pipelines, vector databases, orchestration frameworks like LangChain or Semantic Kernel)

  • Advocate for AI readiness within existing applications and influence the technical direction of future applications

• Engineering Leadership & Team Development

  • Lead and inspire a global team of software enterprise-grade digital manufacturing applications

  • Serve as a hands-on technical mentor guiding junior engineers, facilitating skill growth and fostering a culture of excellence

  • Build an inclusive, collaborative, and high-performance engineering culture centered on ownership, continuous improvement, learning and accountability

  • Establish clear career paths and succession planning within the team

• Governance, Compliance & Performance Management

  • Ensure all solutions adhere to Pfizer’s digital standards, including cybersecurity, GxP, and data integrity requirements

  • Establish and track engineering KPIs – delivery, velocity, system uptime, incident response times, and technical debt reduction

  • Drive transparency through dashboards and regular operational reviews

BASIC QUALIFICATIONS 

• Bachelor’s degree in computer science, software engineering, or relevant experience

• Minimum 8+ years of experience in software engineering, including full-stack or backend development in enterprise environments

• Demonstrated experience leading high-performing engineering teams delivering complex, mission-critical applications

• Strong technical depth in modern software architectures, APIs, microservices, and cloud-native design patterns

• Proven success managing competing priorities, allocating resources effectively, and communicating tradeoffs with senior stakeholders

• Experience mentoring engineers and establishing professional growth and development paths within engineering teams

• Working knowledge of AI technologies and architectures including experience with LLMs, RAG vector databases, orchestration frameworks (e.g. LangChain, Semantic Kernel), or intelligent agent systems

• Strong communication skills with the ability to bridge technical and business audiences

• Demonstrated success operating in global, matrixed organizations

PREFERRED QUALIFICATIONS

• Master’s degree in computer science, Engineering Management or related field

• Experience with regulated or GxP environments such as pharma and medical devices

• Experience in a manufacturing environment

• Familiarity with MLOps and AI infrastructure (e.g. Azure AI Foundry, OpenAI API, Amazon Bedrock and Sagemaker AI, Databricks or similar ecosystems)

• Strong background in agile development, preferabily SaFE, and DevOps culture