Responsibilities

• Design, develop, and optimize LLM-based services for code generation, test automation, and AI copilots.
• Implement RAG workflows to combine internal context (e.g, wikis, APIs, design specs) with LLM capabilities.
• Leverage agentic frameworks to enable AI systems to take intelligent actions (e.g., generate PR-ready code or suggest test coverage improvements).
• Collaborate with engineers, product managers, and platform teams to integrate solutions into VS Code, GitHub, and CI/CD pipelines.
• Own and evolve platform architecture, from prompt engineering to model orchestration and security compliance.

Requirements:

• LLM Integration & Prompt Engineering: Experience building applications on top of GPT-3/4, Claude, or similar.
• RAG Systems: Hands-on expertise in Retrieval-Augmented Generation pipelines, vector stores, and semantic search.
• Cloud Infrastructure: Strong AWS experience (Lambda, S3, EC2, IAM); IaC with Terraform or CloudFormation.

Deep Technical Proficiency

• Python & TypeScript/JavaScript (backend + integrations)
• PyTorch, Transformers, and HuggingFace
• Natural Language Understanding (NLU/NLP) for processing specs, wikis, and design inputs
• API Design, GitHub Webhooks, and VS Code extension APIs

Preferred Experience

• Productionizing AI copilots for internal developer workflows
• Contributing to open-source or internal AI agents/platforms
• Knowledge of engineering tooling or enterprise-grade compliance requirements