Staff AI Engineer (ΑΙ Engineering Excellence)

Use Your Power for Purpose 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. 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. PREFERRED QUALIFICATIONS Experience operating in large-scale, regulated, or enterprise environments. Familiarity with AI governance, model evaluation, observability, and compliance considerations. Experience contributing to shared platforms, internal frameworks, or engineering standards at scale. Work Location Assignment: Hybrid Please apply by sending your CV and a motivational letter in English Purpose Breakthroughs that change patients' lives ... At Pfizer we are a patient centric company, guided by our four values: courage, joy, equity and excellence. Our breakthrough culture lends itself to our dedication to transforming millions of lives. Digital Transformation Strategy One bold way we are achieving our purpose is through our company wide digital transformation strategy. We are leading the way in adopting new data, modelling and automated solutions to further digitize and accelerate drug discovery and development with the aim of enhancing health outcomes and the patient experience. Flexibility We aim to create a trusting, flexible workplace culture which encourages employees to achieve work life harmony, attracts talent and enables everyone to be their best working self. Let’s start the conversation! Equal Employment Opportunity We believe that a diverse and inclusive workforce is crucial to building a successful business. As an employer, Pfizer is committed to celebrating this, in all its forms – allowing for us to be as diverse as the patients and communities we serve. Together, we continue to build a culture that encourages, supports and empowers our employees. Disability Inclusion Our mission is unleashing the power of all our people and we are proud to be a disability inclusive employer, ensuring equal employment opportunities for all candidates. We encourage you to put your best self forward with the knowledge and trust that we will make any reasonable adjustments to support your application and future career. Your journey with Pfizer starts here! Information & Business Tech