Enterprise AI's credibility with the business depends on engineers who can land inside business unit problems, prove value quickly, and hand off cleanly; you will build and lead the function that makes this happen. This is a hands-on leadership role for someone who keeps their judgment grounded in current AI engineering reality: continuing to contribute technically on the most strategic engagements at the frontier of AI-augmented engineering, while building a team that delivers at pace and grows toward greater seniority. Humans steer; agents execute.
Responsibilities
This role will provide YOU the opportunity to lead key activities to progress YOUR career. These responsibilities include some of the following:
Lead the Forward Deployed Engineering function, owning strategy, structure, hiring, development, and standards, with a clear engagement pipeline that delivers at pace.
Hire, mentor, and develop the FDE team, creating development paths from G8 through to G5 with clear milestones and active coaching.
Set the standards for AI-native engineering practice within the function — agentic delivery-automation workflows, delivery bot meshes, prompt and pattern libraries, and handoff hygiene — documented and actively used by the team.
Set the bar for AI, ML, and data science rigor across the function, including evaluation standards, experimental design, and model validation, acting as the final technical authority on modeling approach for strategic engagements.
Own relationships with Director and Senior Director-level business unit sponsors, bringing AI use cases to Enterprise AI and sustaining engagement through the delivery cycle as a credible, high-value partner rather than a vendor.
Take on the most strategic FDE engagements personally, staying hands-on on the engagements that set precedents for the function.
Make and defend portfolio-level kill/continue decisions across FDE engagements with business unit and Enterprise AI leadership, translating AI engineering possibility into business outcomes.
Track the frontier of AI/ML research and translate advances into practical guidance for the team.
Coordinate with Solutions Engineering and Operations Engineering on the delivery pipeline and represent FDE in Enterprise AI leadership forums.
Influence vendor strategy and tooling choices for AI-native engineering practice within Enterprise AI.
Build governance in by design, ensuring the FDE function operates within Code Orange, Responsible AI, and Accountability Report governance from the prototype stage onward, not bolted on afterward.
Report to Enterprise AI leadership on FDE function performance — engagement pipeline, outcomes, team development, and capacity.
Why You?
Basic Qualification
We are seeking professionals with the following required skills and qualifications to help us achieve our goals
12 or more years of experience in software engineering and AI/ML engineering, with significant time leading senior engineering teams or functions.
Bachelor's degree in computer science, Software Engineering, or equivalent practical experience.
Proven track record of taking AI ideas from sketch to working software at speed in customer-facing engineering roles.
Strong technical depth in GenAI patterns, including agents, multi-agent orchestration, RAG, and evaluation.
Recognized expertise in AI, ML, and data science — classical ML, deep learning, LLMs and foundation models, statistical and causal inference, and MLOps at scale — with the credibility to evaluate and challenge modeling decisions across a portfolio of engagements.
Demonstrated daily use of AI coding agents, such as Claude Code, GitHub Copilot, or Databricks AI Assistant, as the primary mode of development, going beyond vibe coding, with experience designing agentic delivery-automation workflows and delivery bot meshes and setting standards for their use across a team.
Experience hiring, mentoring, and developing senior engineering talent, and building an engineering function's structure, standards, culture, and ways of working.
Track record of representing engineering functions to senior business stakeholders.
Preferred Qualification
If you have the following characteristics, it would be a plus
Prior leadership experience at an AI-native company (Anthropic, Palantir, OpenAI, or similar), such as Head of Forward Deployed Engineering, Director of Solutions, or equivalent.
Master's degree in computer science or a related field.
Experience in regulated industries (pharma, healthcare, financial services).
Experience setting AI engineering standards at organizational
#GSK-LI
Skills
AI Frameworks, Algorithm Optimization, Artificial Neural Networks (ANNS), Computer Programming, Deep Learning, Feature Engineering, Google Cloud Platform (GCP) for Machine Learning, Machine Learning Operations, Microsoft Azure Data and AI, ML Frameworks, Model Evaluation, Model Training, Model Validation, Performance Optimizations, Software Development Life Cycle (SDLC)
Please visit GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.
Why GSK?
Uniting science, technology and talent to get ahead of disease together.
GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases – to impact health at scale.
People and patients around the world count on the medicines and vaccines we make, so we’re committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.
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