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aws python rag llm llmops📋 Description
- Set GenAI architecture across the platform, including prompts, RAG, agents, and guardrails.
- Design and build the hardest components; lead high-risk, high-reward bets.
- Sign off on architectural decisions for complex GenAI systems.
- Advise on build-vs-buy for AI infrastructure; justify the rationale.
- Drive cost, latency and throughput optimizations; document trade-offs.
- Define responsible AI principles and governance; align with EU Act and NIST RMF.
🎯 Requirements
- Typically 8+ years building production AI/ML systems; 2+ years in GenAI.
- Strong Python and cloud infra (AWS or equivalent); CI/CD, observability, SLOs.
- Hands-on GenAI stack: LLM APIs, prompt engineering, RAG, multi-agent, eval.
- Deep understanding of LLM capabilities and failure modes; design evals.
- Experience setting architectural standards across multiple teams.
- High-stakes build-vs-buy judgments with proven results.
- Strategic grasp of responsible AI aligning with NIST EU Act.
🎁 Benefits
- Great work-life balance
- Office location with regular social events, office drinks and free snacks
- Flexibility to work from home up to 1 day per week
- Stock options
- Pension scheme with NEST
- Personal development budget and health insurance through BUPA and fitness discounts
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