AI Engineer

🔥 0 minutes ago

🇦🇷 Argentina – Remote

⏰ Full Time

🟠 Senior

🔴 Lead

🤖 AI Engineer

👻 Ghost score 21%

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Logo of Jeeves

Jeeves

51 - 200 employees

💼 Consulting

📦 Logistics

📣 Marketing

Consulting • Logistics • Marketing

Jeeves is a financial platform offering streamlined solutions for global finance management. It allows companies to issue cards, send payments, and manage expenses through an all-in-one platform available in over 25 countries globally. By integrating various financial services, Jeeves increases efficiency and saves costs for businesses traditionally burdened by disjointed financial systems. With offerings such as international fund transfers, competitive FX rates, expense management, and direct accounting integrations, Jeeves enhances operational capabilities across multiple currencies and regions. Although not a bank, it partners with licensed banks and financial institutions to provide these services.

📋 Description

• Own finance workflows end to end, from problem definition through production and ongoing improvement • Design agentic and LLM-based systems combining extraction, retrieval, reasoning, and tool use, with human-in-the-loop points for high-value financial decisions • Write design documents, make build-vs-buy and model choices, and set workflow success metrics • Engage directly with customers and internal finance users to understand workflow problems and define completion criteria • Build production-grade 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 re-ranking • Integrate AI services with Jeeves's backend using API contracts, retries, graceful degradation, and per-customer data isolation • Manage model cost and latency • Build evaluation sets and automated evaluations; detect regressions when prompts, models, or data change • Instrument AI components with logging, tracing, dashboards, and alerts • Maintain an audit trail of AI decisions for a regulated financial product • Establish shared AI engineering patterns, tooling, and practices • Demonstrate effective use of coding agents and AI tools to the wider team • Review AI system designs and share learnings

🎯 Requirements

• 7+ years of professional software engineering experience, including at least 2 years building and operating LLM or AI-powered systems in production • A track record of owning a large system or workflow end to end, from scoping and design through launch and iteration, with limited direction • Hands-on experience shipping LLM-powered applications with APIs such as Anthropic, OpenAI, or similar, including structured outputs, error handling, and evaluation • Experience designing agentic or multi-step AI workflows (tool use, orchestration, human review steps), or RAG systems with vector databases such as pgvector, Pinecone, or Weaviate • Strong proficiency in Python, plus solid backend fundamentals: REST APIs, PostgreSQL or similar relational databases, async patterns, and a major cloud provider (AWS, GCP, or Azure) • Uses AI coding agents and tools (for example Claude Code, Cursor, or Codex) as a regular part of how they build, and can explain where they help and where they don't • Experience with observability for AI systems: logging, tracing, dashboards, and quality monitoring • Professional fluency in English, written and spoken

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