Sr Engineering Manager, Core GenAI Services

ROLE SUMMARY

The Sr Engineering Manager Core GenAI Servicesis a pivotalsenior technical leadershiprole reporting to the VP R&D Technology Ecosystem. This role demands a unique combination of deep hands-on architecturalexpertise strategic vision andpeopleleadership grounded in a proven ability to lead distributed engineering teams across diverse complex technical landscapes.

You willdrive the strategy design and operational execution for the organizations core internal GenAI capabilities specifically owning theCore GenAI Servicesand theGenAI Gatewaya centralized API service that provides secure standardized and scalable access to GenAI models (LLMs SLMs) and orchestration frameworks for internal teams across the R&D landscape.

Success in this position requires a leader with a proventrack recordofAI transformation upskilling and mentoring capable of translating complex business needs in the pharmaceutical space into technical decisions that unlock massive scale and adoption.You will shape and continuously refine the internal engineering culture championing principles of extreme ownership (you build it you own it) and accelerating delivery through rapid feedback loops.

ROLE RESPONSIBILITIES

Senior Leadership & Strategy

• Driving GenAI Strategy:Define and own the long-term vision and technical strategy for internal Core GenAI capabilities ensuring alignment with enterprise AI goals and R&D business priorities.

• AI Transformation & Upskilling:Lead the organizational AI transformation efforts including upskilling and capability development across engineering andR&Dteams.

• Advanced Communication & Stakeholder Alignment:Leveragestrong communicationskills and experience interacting with senior customer and business stakeholders to drive consensus and adoption.

• Standards & Best Practices:Drive standards playbooks and global best practices for LLMs SLMs retrieval-augmented generation (RAG) orchestration frameworks and GenAI architectures specifically tailored for the highly regulated pharmaceutical space.

Technical Leadership & Architecture (GenAI Gateway)

• Core GenAI Ownership:Own the architecture and development of the Core GenAI Services and the high-performance centralized GenAI Gateway ensuring resilience security and low-latency API access for all consuming teams.

• Deep GenAI Expertise:Provide hands-on architectural depth based on a deep understanding of GenAI technologies (LLMs SLMs RAG AI agents orchestration frameworks) and modern software/cloud architectures.

• AIProductionization:Applyexpertisein productionizing complex AI-based systemsleveragingexperience from diverse domains including Computer Vision and Security applications including robust evaluation deployment monitoring and governance frameworks (MLOps).

• Architectural Evolution:Own and evolve the platform architecture and technical strategy ensuring scalability reliability security and cost efficiency across the cloud footprint.

People Leadership & Culture

• Team Building:Build and lead a high-performing technical team of software engineers machine learning engineers anddevops/infrastructure engineers.

• Mentorship & Development:Actively mentor and develop our internal engineering talent pool providing technical coaching that deepensexpertisein AI/ML systems and platform engineering.

• Cultural Definition:Define and evolve the internal engineering culture championing extreme ownership high quality data-driven decision-making and short iterative feedback cycles.

• Talent Growth:Lead mentor and grow teams of individual contributors and team leads fostering a culture of technical excellence continuous learning and structured career development.

Platform Engineering & Developer Enablement

• Oversee the development of reusable SDKs APIs CLI tools and developer platforms to maximize the adoption of GenAI capabilities.

• Drive creation of reusable components frameworks and infrastructure that accelerate the full GenAI model lifecycle workflows.

• Champion developer experience and platform adoption through high-quality documentation enablement and direct feedback loops with consuming teams.

QUALIFICATIONS

BASIC QUALIFICATIONS

• 15 yearsof hands-on software engineering experience with deepexpertisein system architecture platform development andproductionAI/ML systems.

• 10 yearsof progressive leadership and people management experience (including managing managers or sub-teams).

• Demonstratedexpertisein productionizing AI-based systems and scaling them for enterprise use across multiple high-stakes domains (e.g. Computer Vision Cybersecurity GIS).

• Expert-level production Python and extensive cloud (AWS) architecture experience designing complex scalable GenAI systems.

• Deep understanding of GenAI technologies (LLMs SLMs RAG orchestration frameworks) and modern software/cloud architectures.

• Proven stakeholder management executive communication and cross-functional delivery in complex regulated environments.

• Bachelors orMasters degree in Computer Science Engineering AI/ML ora relatedtechnical field.

PREFERRED QUALIFICATIONS

• Experience defining GenAI standards playbooks and best practices inthe pharmaceutical healthcare or other highly regulated industries.

• Track recordof building and leading world-class multi-disciplinary technical teams (SWEs MLEs DevOps).

• Demonstratedexpertisein fields directly applicable to R&D such as Computer Vision Geospatial Information Systems (GIS) or robust AI systems in a high-security context.

• Experience with advanced LLM frameworks and services (e.g. Anthropic Claude Azure OpenAI Amazon Bedrock) and orchestration tools (LangChainLlamaIndex).

• Advanced knowledge of AWS services microservices event-driven architectures and distributed systems.

• PhD in Computer Science AI/ML or related field.