Coforge
Forward Deployed Graduate Engineer
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Role: Forward Deployed Graduate Engineer
Key Skills: LLMs, Agentic AI, Production AI, RAG, Python, Cloud & APIs
Experience: 0 - 2 years
Location: London, UK
About the Team
The Coforge FDE Practice is the tip of the spear for our enterprise AI work. Our Forward Deployed Engineers embed with Fortune 500 clients across Financial Services, Insurance, Healthcare, Travel, and Retail to take AI from an "interesting pilot" to "production system that moves a business metric." We're scaling the practice over the next year, and we're hiring a founding cohort of FDEs to build that scale-up alongside us.
About the Role
- Join a 60–90-day intensive program to build a foundation in applied AI engineering (LLMs, RAG, agentic systems, evaluations), vertical immersion, and a client-mirrored capstone.
- Work alongside Senior FDEs from day one, contributing to real projects instead of classroom-style learning.
- Embed with enterprise clients (typically Fortune 500) to deliver production AI systems in 2–4-week sprints.
- Co-own workstreams covering agentic workflows, RAG pipelines, eval frameworks, fine-tuning, or AI-led transformation of legacy systems.
- Build and ship production-grade code from day one for real users.
- Present weekly updates to stakeholders (engineering to C-suite), including readouts, demos, and design defense.
- Translate ambiguous client problems into deployed AI solutions without predefined specifications.
- Progress to owning workstreams independently (~9-12 months) and leading deployments (~18-24 months).
- Mentor incoming associates and support their onboarding.
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Requirements:
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- BS/MS in Computer Science, Engineering, Math, Statistics, Physics, or similar STEM field (or equivalent proven self-taught expertise with public portfolio).
- Strong Python skills with ability to read modern programming languages.
- Experience building applications using LLM APIs (OpenAI, Anthropic, Google) with understanding of RAG, embeddings, vector retrieval, and evaluations.
- Daily user of AI coding tools (e.g., Cursor, Copilot, Claude Code).
- Familiarity with Git, CI/CD basics, Docker, and working in collaborative codebases.
- Ability to write concise executive-level one-page documents.
- Ability to present technical concepts clearly to non-technical audiences.
- Experience with agentic frameworks (LangGraph, CrewAI, AutoGen, Mastra, OpenAI Agents SDK, MCP).
- Exposure to fine-tuning methods (LoRA, full fine-tuning, RLHF basics).
- Familiarity with evaluation and observability tools (LangSmith, Braintrust, Arize, Weights & Biases).
- Hands-on experience or certification in AWS, Azure, or GCP.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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