Position Summary
GSK's Enterprise AI team builds AI solutions that prove value fast and scale to production. Forward Deployed Engineering is the front of the Enterprise AI delivery pipeline — proving AI ideas with the business through PoCs, PoVs, MVPs, and, where appropriate, first production versions, before handing proven solutions to Solutions Engineering for scale-up — bringing to GSK a model proven by AI-native companies such as Anthropic, Palantir, and OpenAI.
You will act as the most senior technical authority in the FDE function, operating at enterprise scope with two equal mandates: setting the standards for AI-native, enterprise-level development across GSK — architecture, agentic delivery-automation workflows, delivery bot meshes, evaluation, and governance — and owning FDE delivery outcomes for a defined portfolio of strategic business units.
This is a senior technical leadership role for someone who leads through technical credibility: staying hands-on at the frontier of AI-augmented engineering, leading Staff and Senior FDEs on the most consequential engagements and shaping how AI engineering is done well beyond the FDE team. As Enterprise AI scales, the value of each engagement increasingly depends on what it leaves behind: you will set standards from real delivery experience, prove them inside the business units that matter most, and serve as the escalation point for the hardest architecture, ML, and agentic-engineering decisions. 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:
- Define and own enterprise-level development standards for AI solutions across GSK — reference architectures, agentic delivery-automation workflows, delivery bot meshes, evaluation frameworks, and handoff hygiene — adopted by FDE, Solutions Engineering, and Operations Engineering alike.
- Set the enterprise technical direction for AI-native engineering, going well beyond vibe coding to establish how agentic workflows and delivery bot meshes are designed, secured, monitored, and reused at scale.
- Own the enterprise pattern library and reference platform, ensuring reusable agents, prompt templates, MCP integrations, and reference architectures are good enough that teams across GSK adopt them without rework.
- Chair FDE technical design review and contribute to Enterprise AI architecture governance, approving, challenging, or redirecting high-impact technical decisions.
- Own FDE delivery for a defined portfolio of strategic business units — engagement pipeline, prioritization, quality, and outcomes from intake to clean handoff.
- Lead the most complex, precedent-setting engagements personally, staying hands-on in problem framing, architecture, and prototype delivery.
- Lead multi-FDE engagement teams, directing Staff, Senior, and Engineer-level FDEs across concurrent engagements within assigned business units.
- Partner with Director and VP-level business unit leaders, shaping their AI roadmaps, qualifying the highest-value use cases, and making and defending kill/continue decisions with multi-year business consequences.
- Act as the technical authority and escalation point for the FDE function on architecture, ML, data science, and agentic engineering.
- Mentor and grow Staff and Senior FDEs, shaping the technical career path toward Principal and raising the technical bar of the function.
- Calibrate the technical hiring bar — leading senior technical interviews and setting the standard for senior FDE hires.
- Partner with Enterprise Architecture, Data Platforms, Cyber Security, and Tech functions, aligning FDE standards with enterprise platforms so prototypes are built to scale.
- Influence vendor strategy and tooling choices, evaluating and shaping the adoption of AI models, agent frameworks, and developer tooling at enterprise scale.
- Represent GSK's AI engineering practice externally through industry forums, partner relationships, and technical publications where appropriate.
- Build governance in by design, embedding Code Orange, Responsible AI, and Accountability Report requirements into enterprise development standards so governance is part of every engagement, not bolted on.
- Report to Enterprise AI leadership on standards adoption, business unit delivery outcomes, and technical risk across the portfolio.
Why You?
Basic Qualification
We are seeking professionals with the following required skills and qualifications to help us achieve our goals
- 15 or more years of experience in software engineering and AI/ML engineering, including principal-level technical leadership across multiple teams or an enterprise.
- Bachelor's degree in computer science, Software Engineering, or equivalent practical experience.
- Demonstrated track record of setting engineering standards, reference architectures, or platforms that were adopted at organizational or enterprise scale.
- Proven track record of taking AI ideas from sketch to working software and production at speed in customer-facing or embedded engineering roles, and leading delivery across a portfolio of business stakeholders.
- Understanding of hands-on expertise in GenAI patterns, including agents, multi-agent orchestration, RAG, prompt engineering, evaluation, fine-tuning, and Model Context Protocol (MCP) integrations.
- Enterprise-level expertise in AI, ML, and data science — classical ML, deep learning, LLMs and foundation models, statistical and causal inference, and MLOps at scale — sufficient to set modeling and evaluation standards across an organization.
- Demonstrated daily use of AI coding agents, such as Claude Code, GitHub Copilot, or Databricks AI Assistant, as the primary mode of development, with a track record of architecting agentic delivery-automation workflows and delivery bot meshes and defining enterprise standards for their use.
- Experience influencing and partnering with Director and VP-level business and technology leaders.
- Prior responsibility for mentoring Staff- and Senior-level engineers and shaping senior technical career paths.
Preferred Qualification
If you have the following characteristics, it would be a plus
- Principal, Distinguished, or Head of Forward Deployed Engineering-level experience at an AI-native company (Anthropic, Palantir, OpenAI, or similar) or a hyperscaler.
- Master's or PhD in Computer Science, Machine Learning, or a related quantitative field.
#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 Algorithms, Machine Learning Operations, Microsoft Azure Data and AI, ML Frameworks, Model Evaluation, Model Training, Model Validation, Performance Optimizations, Software Development Life Cycle (SDLC)
• If you are based in Cambridge, MA; Waltham, MA; Rockville, MD; or San Francisco, CA, the annual base salary for new hires in this position ranges $205,425 to $342,375. The US salary ranges take into account a number of factors including work location within the US market, the candidate’s skills, experience, education level and the market rate for the role. In addition, this position offers an annual bonus and eligibility to participate in our share based long term incentive program which is dependent on the level of the role. Available benefits include health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and paid caregiver/parental and medical leave. If salary ranges are not displayed in the job posting for a specific country, the relevant compensation will be discussed during the recruitment process.
Please visit GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.
