What you'll do

• Design and ship agentic, multimodal, evaluation-driven product features across extraction, reasoning, generation, and orchestration.
• Work on document intelligence problems: OCR, structured extraction, chunking, layout-aware parsing, and PDF-to-schema workflows.
• Design and ship RAG pipelines (LlamaIndex) using vector databases, hybrid retrieval, reranking, and structured context assembly.
• Integrate hosted LLM APIs (OpenAI, Google Gemini) and, where needed, smaller self-hosted models (served with vLLM) into product features.
• Build scalable inference services using batching, streaming, caching, and other latency/cost optimizations.
• Implement production pipelines for evaluation, prompt/version management, and deployment, with offline evals and regression datasets for accuracy, latency, and reliability.
• Own AI-related infrastructure in Docker, Cloud Run, and GCP, with proper logging, monitoring, and observability.

What You Bring

• 8+ years of engineering experience, with a track record of owning systems in production.
• Deep Python — you build solid services (FastAPI) with sensible tests and understand how it works under the hood. Not "I write scripts."
• Pragmatic delivery. Clean, enterprise-grade code matters — but shipping a working result in a reasonable timeframe matters more. You know when "good enough" ships, and you don't gold-plate.
• Proven experience building agentic / LLM systems in production — not just prototypes. You know the real-world traps: frameworks, memory, streaming, evals, cost, latency.
• Hands-on experience integrating OpenAI / Gemini APIs into real user-facing products.
• Practical experience with RAG systems: chunking, embedding pipelines, vector search, reranking, context construction, and hallucination reduction.
• Experience with vector stores (pgvector, Qdrant) and hybrid search; judgment on when retrieval helps and when a deterministic pipeline is better.
• Familiarity with document understanding workflows: OCR, PDF parsing, table/form extraction, normalization of messy real-world inputs.
• DevOps & MLOps at a real level — containers, GCP, CI/CD; plus the MLOps side: model serving, eval pipelines, and LLM tracing/observability. You own your systems end to end instead of paging infra for every change.
• Strong communication and collaboration, comfortable working remote/async, self-motivated.

Working with us

• 🌏 100% remote, work from anywhere
• ✈️ Regular meetups and offsites
• ⚡️ No micromanagement
• 🏖 Unlimited time off
• 🧠 Work with professionals
• 📚 Growth investment
• 🤖 Working on the AI frontier (Claude Code, Cursor, Codex, MCPs)
• ❤️ Wellbeing (Health & Wellness Stipend, Mental Health Support)

Salary & Contract

$90,000–$132,000/year gross, paid via deel.com

How to apply?

1. Submit CV.
2. We'll invite you for a 1-hour screening call.
3. We'll invite you for a 1-hour technical interview.
4. If we see a potential match, we might ask you to complete a small challenge that requires up to 8 hours of your time.
5. Receive the offer 🎉