AI RAG Engineer

We are a fast-moving startup building intelligent systems powered by large language models. We are looking for a software engineer who can design, build, and deploy AI systems end-to-end — especially those involving retrieval-augmented generation (RAG), embeddings, and LLM orchestration. This is a hands-on role with real impact and ownership.

What You’ll Work On

• Architect and implement RAG pipelines that combine vector search, custom retrievers, and LLM reasoning
• Own the evaluation stack — design eval harnesses, benchmarks, and regression tests for LLM outputs
• Build and scale infrastructure for deploying models and agents into real production environments
• Experiment with model behavior, latency trade-offs, and prompt tuning
• Collaborate closely with founders on product, architecture, and research priorities

Core Requirements

• Proven experience building AI systems with LLMs — you’ve worked with tools like LangChain, LlamaIndex, Haystack, or built your own stack
• Hands-on with embedding models, vector DBs (e.g., FAISS, Weaviate, Qdrant), and retrieval logic
• Strong Python engineering skills — you write clean, production-ready code with tests
• Experience building and evaluating RAG pipelines in a real-world setting
• Familiarity with LLM evaluation techniques — you don’t deploy until you’ve tested against real metrics
• Solid understanding of modern cloud infrastructure (e.g., Docker, Kubernetes, serverless, GCP/AWS)

Bonus Skills

• Built custom eval pipelines using tools like Ragas, TruLens, or your own scoring systems
• Experience tuning open-source models (e.g., Mistral, LLaMA, Falcon) or working with APIs (OpenAI, Anthropic, Cohere)
• Exposure to agentic systems, tools + memory management, or multi-step reasoning chains
• Experience in fast-paced, early-stage startup environments

Why This Role Is Unique

• You’ll be engineering AI features that ship to users, not just running experiments
• Evaluation is first-class — we’re serious about quality, not just 'it looks good in the demo'
• You’ll help shape both tech strategy and engineering culture from day one
• We care more about what you’ve built than where you’ve worked

You should apply if: You’re an engineer who enjoys building production-grade AI systems, and you believe evals, not vibes, should drive development. You’re comfortable moving fast, debugging strange model behavior, and taking real ownership of the tech.

Note, this company is sponsoring visas.