Oversee multiple concurrent development initiatives 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 outcomes with product roadmaps
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 maintainable 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
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
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
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.
Requirements
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.
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