Jeeves
Jeeves
Jeeves yra finansų platforma, padedanti įmonėms vienoje vietoje valdyti tarptautines išlaidas ir mokėjimus. Jos paslaugos apima įmonių kortelių išdavimą, išlaidų valdymą, tarptautinius pervedimus, valiutos keitimą ir tiesiogines integracijas su apskaitos sistemomis. Šios paslaugos padeda vykdyti veiklą daugiau nei 25 šalyse ir naudoti kelias valiutas. Sujungdama šias funkcijas, Jeeves padeda įmonėms mažiau priklausyti nuo atskirų finansinių įrankių ir pagerinti kasdienes finansų operacijas. Įmonė nėra bankas – savo paslaugas ji teikia bendradarbiaudama su licencijuotais bankais ir kitomis finansų įstaigomis.

Senior AI Engineer, Remote in Argentina

Lead production LLM workflows for Jeeves’ stablecoin banking platform, building AI systems that automate finance operations. Develop, evaluate, and monitor tools that support financial decisions.

Aprašymas

  • Lead finance workflows from initial problem definition through production and continuous improvement.
  • Design agentic and LLM systems that combine extraction, retrieval, reasoning, and tool use, with human review for high-value financial decisions.
  • Document system designs, choose whether to build or buy and which models to use, and define workflow success metrics.
  • Work directly with customers and internal finance teams to understand workflow needs and set completion criteria.
  • Build production-ready LLM pipelines with prompt and context design, structured outputs, validation, fallbacks, and confidence scoring.
  • Design retrieval and RAG components, including chunking, embeddings, vector search, and reranking.
  • Connect AI services to Jeeves’ backend through API contracts, retries, graceful degradation, and customer-level data isolation.
  • Manage model costs and response times.
  • Create evaluation datasets and automated tests, and identify regressions when prompts, models, or data change.
  • Add logging, tracing, dashboards, and alerts to AI components.
  • Maintain records of AI decisions for a regulated financial product.
  • Set shared patterns, tools, and practices for AI engineering.
  • Show the wider team effective ways to use coding agents and other AI tools.
  • Review AI system designs and share lessons learned.

Reikalavimai

  • Bring at least seven years of professional software engineering experience, including two or more years building and operating production LLM or AI systems.
  • Have owned a substantial system or workflow from scoping and design through launch and iteration, with little oversight.
  • Have hands-on experience shipping LLM applications using Anthropic, OpenAI, or similar APIs, including structured outputs, error handling, and evaluation.
  • Have designed agentic or multi-step AI workflows with tool use, orchestration, or human review, or RAG systems using vector databases such as pgvector, Pinecone, or Weaviate.
  • Be proficient in Python and strong in backend fundamentals, including REST APIs, PostgreSQL or a comparable relational database, asynchronous patterns, and a major cloud platform such as AWS, GCP, or Azure.
  • Regularly use AI coding tools such as Claude Code, Cursor, or Codex, and be able to explain their strengths and limitations.
  • Have experience monitoring AI systems through logging, tracing, dashboards, and quality metrics.
  • Be professionally fluent in spoken and written English.

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