Engineer II – Forward Deployed Engineer

Overview

In this role you will own enterprise AI engagements end-to-end, embedding with BU teams to prototype AI solutions at a rapid cadence and hand them off to Solutions Engineers. You will mentor junior engineers, shape intake and standards for FDE work, and drive reusable AI patterns. The position combines technical depth with stakeholder influence to deliver production-ready AI in a fast-paced, production-focused environment. You will operate at the intersection of engineering excellence and business impact, contributing to GSK’s mission to get ahead of disease through AI-powered solutions.

Pay / Benefits

• annual bonus
• share-based long term incentive program
• health care and family insurance
• retirement benefits
• paid holidays and vacation
• paid caregiver/parental and medical leave

Responsibilities

• Own BU use cases from problem framing to working prototype at days-to-weeks cadence with minimal supervision
• Qualify incoming BU asks, define scope and feasibility before engagement
• Embed with BU teams to build trusted domain understanding
• Form and defend kill/continue recommendations based on evidence
• Ship production-ready versions and hand off to Solutions Engineer
• Lead small multi-FDE engagements and review outputs for quality
• Mentor G8 FDEs and contribute to onboarding processes
• Operate AI agent workflows and validate AI-generated code
• Package proven use cases for Solutions Engineer with architecture and open risks
• Maintain high-quality FDE pattern library contributions
• Initiate governance conversations (Code Orange, Responsible AI, Accountability) from prototype stage
• Coach BU engineers on AI-augmented ways of working
• Contribute to defining FDE engagement standards

Key requirements

• Bachelor’s degree in Computer Science, Software Engineering, or equivalent practical experience
• 3+ years of full-stack software engineering or AI/ML engineering experience with production deployments
• Proficiency in Python and at least one other language (e.g., TypeScript, JavaScript, Go)
• Experience developing generative AI solutions (agents, multi-agent orchestration, RAG, prompt engineering, evaluation)
• Experience with ML/DL models using PyTorch or TensorFlow
• Experience with data pipelines and platforms like Databricks or Apache Spark
• Experience using AI-assisted development tools (e.g., Claude Code, GitHub Copilot, Databricks AI Assistant)
• Experience building agentic workflows and multi-agent systems
• Experience guiding or mentoring engineers (formal leadership or delivery leadership)

• Stakeholder management
• Mentoring and coaching
• Clear communication
• Python
• TypeScript/JavaScript/Go
• Generative AI techniques (agents, multi-agent systems, RAG)

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