Sr Engineering Manager, Core GenAI Services

ROLE SUMMARY 

The SrEngineering Manager, Core GenAI Services, is a pivotal, senior technical leadership role reporting to the VP, R&D Technology Ecosystem. This role demands a unique combination of deep, hands-on architectural expertise, strategic vision, and people leadership, grounded in a proven ability to lead distributed engineering teams across diverse, complex technical landscapes. 

You will drive the strategy, design, and operational execution for the organization's core internal GenAI capabilities, specifically owning the Core GenAI Services and the GenAI Gateway—a 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 proven track record of AI 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 and R&D teams. 

• Advanced Communication & Stakeholder Alignment: Leverage strong communication skills 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. 

• AI Productionization: Apply expertise in productionizing complex AI-based systems, leveraging experience 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, and devops/infrastructure engineers. 

• Mentorship & Development: Actively mentor and develop our internal engineering talent pool, providing technical coaching that deepens expertise in 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+ years of hands-on software engineering experience with deep expertise in system architecture, platform development, and production AI/ML systems. 

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

• Demonstrated expertise in 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. 

• Bachelor’s or Master’s degree in Computer Science, Engineering, AI/ML, or a related technical field. 

PREFERRED QUALIFICATIONS 

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

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

• Demonstrated expertise in 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 (LangChain, LlamaIndex). 

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

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