Senior Python AI Engineer

About The Position

Klarna's commercial and go-to-market teams move fast. Our AI engineering team builds the systems that power them, from intelligent document processing to automated decision pipelines, and we own those systems end-to-end, from prototype to production. This is a senior individual-contributor role on a small, high-ownership team. You will work directly with commercial, legal, and sales stakeholders to scope and ship AI-powered automation that replaces manual work at scale.

What You'll Do

• Design and build AI-powered automation across the commercial stack: Request for Proposal (RFP) generation, contract analysis, lead routing, supplier deduplication, and structured data extraction from unstructured documents
• Own projects end-to-end in time-boxed cycles: scoping (1–2 weeks) → building → deploying → monitoring → iterating, with full accountability from prototype to production and no handoffs
• Instrument everything you ship: cost tracking, latency monitoring, quality metrics, and rigorous evaluation pipelines are non-negotiable parts of every system, not afterthoughts
• Define and enforce accuracy and data-governance standards for contract and legal automation workflows, including guardrails, hallucination controls, and audit trails
• Collaborate directly with product, sales, legal, and commercial operations to translate ambiguous business problems into well-scoped technical solutions
• Present technical decisions and tradeoffs clearly to senior leadership (CCO, GTM executives), written and verbal, and make complex work legible to non-technical stakeholders

Who You Are

• Genuinely passionate about AI: you keep up with model releases, API updates, and evolving best practices from the research and engineering community as a matter of habit, not obligation
• Deep AI systems knowledge: hands-on experience with OpenAI and Anthropic APIs, advanced prompt engineering, and agent architectures; you understand how to structure codebases so that AI systems (including coding agents) operate reliably and at scale
• Senior Python Engineer: approximately 5+ years building production-grade Python applications; strong foundation in FastAPI or a comparable framework for building REST services; solid grasp of relational databases (e.g. PostgreSQL) and vector databases
• Production-minded: you treat observability, evaluation, cost optimisation, and quality monitoring as first-class engineering concerns; you have maintained live AI systems while shipping new features in parallel
• Business-oriented: you ask why before how; you work directly with commercial stakeholders to frame problems correctly, and you're as comfortable in a requirements meeting as you are in a code review
• Iterative and fast: you ship MVPs in 1–2 week cycles, use real feedback to validate direction quickly, and actively close the gap between product intent and working software
• Strong communicator: you produce clear written summaries of complex technical work for mixed audiences; you default to async-first, written communication and make your work visible and legible to the team

Awesome to have

• Experience with advanced RAG architectures: query rewriting, reranking, hybrid search, or agentic RAG patterns, and familiarity with vector databases such as PgVector, Pinecone, or Weaviate
• Deep familiarity with LangSmith or an equivalent platform for traceability, evals, and production debugging of LLM systems
• Background working in sales, legal, or commercial operations contexts; you understand the domain, not just the tooling
• JavaScript / TypeScript for lightweight frontend or integration work
• Graph database experience (e.g. Neo4j) for relationship-heavy data problems
• Track record of rescoping or shutting down projects that aren't delivering value, and communicating that decision clearly to stakeholders

Please include a CV in English.

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