Lead, Forward Deployed Engineer

What You Will Do

• Plan and direct the work of Forward Deployed Engineers across concurrent projects: allocating tasks, sequencing dependencies, and tracking delivery against schedule and cost
• Run technical discovery with client stakeholders and convert it into a solution architecture your engineers can build against
• Architect end-to-end generative AI solutions covering LLM training, deployment, and RAG workflows
• Build and optimise scalable infrastructure and pipelines for AI training, inference, and experimentation
• Own technical decisions and risk within scope, escalating platform-level trade-offs to the Forward Deployed Architect
• Embed proactive monitoring, access controls, authentication, and encryption into production AI systems
• Mentor engineers through code and design review, pairing, and structured feedback, and lead knowledge-sharing across the team
• Lead or co-author at least one Q1/Q2 journal paper each year, and help your engineers turn delivery insight into publishable work

What You Will Bring

• Advanced proficiency in Python and at least one systems language (C++, Go, or Rust), with deep working knowledge of ML/AI frameworks such as PyTorch and TensorFlow and of agentic orchestration tooling
• Experience with microservices, container orchestration (Kubernetes, Docker), and cloud platforms for large-scale training and inference workloads
• Experience deploying and maintaining large-scale HPC/AI clusters, including GPU hardware and software (DGX, CUDA, InfiniBand or RoCE)
• Strong Linux, networking, and OS-level security fundamentals, plus CI/CD tooling such as GitLab, GitHub Actions, or Jenkins
• Demonstrated experience leading small AI or software project teams in a global, multicultural environment
• Hands-on agile delivery: sprint planning, estimation, backlog prioritisation, and delivery tracking
• Practical experience building or fine-tuning large language models and generative AI systems, and the judgement to know when fine-tuning is not the right answer
• The judgement to know when a client requirement should be pushed back on rather than built

Qualifications

Minimum Bachelor’s or Master’s in Computer Science, Artificial Intelligence, Machine Learning, or a related field, with 3–5 years in an AI-focused role.

Nice to Have

Experience delivering into regulated or security-reviewed client environments, including data residency and audit requirements; distributed training frameworks including but not limited to DeepSpeed, Megatron, or Ray; experience scoping and estimating new work alongside a business development team; formal mentoring or line management experience.