IT & Software

Senior, Forward Deployed Engineer (Agentic Automation for CMC R&D)

GSK

London · Greater London · United Kingdom

Overview

Senior Forward Deployed Engineer embedded with BU teams to rapidly validate AI ideas through PoCs/PoVs/MVPs, delivering production-grade prototypes and shaping AI-enabled processes in GSK’s CMC R&D. You will work hands-on with data analytics and process science teams, turning manual workflows into agentic automation while mentoring peers. This role offers a direct path from prototype to scale and a stake in reducing time to impact for safer, faster medicines.

Pay / Benefits
  • learning and development opportunities
  • supportive team culture
  • impact on healthcare outcomes
  • inclusive work environment
  • hybrid working (UK)
Responsibilities
  • Own high-priority BU use cases from framing to working prototype at days-to-weeks cadence
  • Deliver production-ready prototypes where path is clear and hand off to scale-up with Sr. Solutions Engineer
  • Operate AI agent workflows for autonomous prototype delivery and rely on AI coding assistants for development
  • Embed with BU teams, prototype against real data and workflows, and hand off with architecture rationale and risks
  • Contribute to governance: Code Orange, Responsible AI, and accountability discussions during prototyping; share reusable patterns and templates
  • Coach BU engineers on AI-augmented ways of working and build BU capability alongside delivery outcomes
Key requirements
  • Strong experience in full-stack or AI/ML engineering with production deployments
  • Proficiency in Python and TypeScript/JavaScript, Go, or equivalent
  • Ability to translate ideas into working software with R&D scientists as end users
  • Hands-on experience with agent frameworks, multi-agent orchestration, MCP, and agent evaluation/tracing
  • Experience automating scientific or technical workflows with agents and data pipelines from lab/process systems
  • Daily use of AI coding agents (Claude Code, GitHub Copilot, Databricks AI Assistant) for development
  • Collaborative and user-centric mindset
  • Judgement and risk awareness in prototyping and handoffs
  • Ability to communicate complex ideas clearly to BU and leadership
  • Agent frameworks and multi-agent orchestration
  • Model Context Protocol (MCP)
  • Data pipelines from lab and process systems

Reference: WJ-747_31164200

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