Job Title: Forward Deployed Engineer (Graduate)
Location: London, UK (Hybrid)
Experience: 0-2 Years
Key Skills: Python, LLM APIs (OpenAI, Anthropic, Google), RAG, Agentic AI, Cursor, GitHub Copilot, Claude Code, Docker, CI/CD
Join Coforge's AI Innovation Team
We at Coforge are looking for passionate and ambitious graduates to join our Forward Deployed Engineering (FDE) Practice. This is a unique opportunity to work directly on enterprise AI initiatives, helping Fortune 500 clients transform innovative AI concepts into production-grade solutions.
If you're passionate about AI, enjoy solving complex problems, and want to build production-grade solutions for global enterprises, we'd love to hear from you.
What You'll Do
- Participate in an intensive AI engineering program focused on LLMs, RAG, agentic systems, and AI evaluations.
- Collaborate with senior engineers on real-world client engagements from day one.
- Design, develop, and deploy production-ready AI applications.
- Build agentic workflows, RAG pipelines, evaluation frameworks, and AI-driven modernization solutions.
- Present project updates, demos, and technical recommendations to stakeholders.
- Translate complex business challenges into scalable AI solutions.
- Grow into independently leading AI workstreams and client deployments.
Required Skills & Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics, Physics, or a related STEM discipline.
- Strong Python programming skills.
- Practical experience with LLM APIs such as OpenAI, Anthropic, or Google.
- Understanding of RAG, embeddings, vector databases, retrieval systems, and AI evaluations.
- Regular user of AI coding tools such as Cursor, GitHub Copilot, or Claude Code.
- Knowledge of Git, CI/CD practices, Docker, and collaborative software development.
- Strong communication and stakeholder management skills.
Preferred Skills
- Experience with agentic AI frameworks such as LangGraph, CrewAI, AutoGen, MCP, or OpenAI Agents SDK.
- Exposure to fine-tuning techniques including LoRA and RLHF concepts.
- Familiarity with observability and evaluation tools such as LangSmith, Braintrust, Arize, or Weights & Biases.
- Hands-on experience or certifications in AWS, Azure, or Google Cloud Platform.
If you're passionate about AI, enjoy solving complex problems, and want to build production-grade solutions for global enterprises, we'd love to hear from you.
