Senior AI Engineer

About the role

Jeeves is the stablecoin-native banking platform for global enterprises. Thousands of companies across 35 countries run their corporate cards, payments, treasury and spend on one platform, with more than $5B in annualized volume, payouts to 190 countries, and one of the fastest-growing stablecoin payment networks in the world. Customers include BMW, H&M, Lululemon, Burger King, Kavak and XP, and more than 80% of customers use multiple Jeeves products. Jeeves has raised more than $400 million in equity funding from Andreessen Horowitz, Y Combinator, CRV, Coinbase Ventures, GIC, AllianceBernstein, CoinFund and others. This role is remote based out of the United States.

Responsibilities

• Own AI Workflows End to End: Design agentic and LLM-based systems that combine extraction, retrieval, reasoning, and tool use to complete multi-step work, with clear human-in-the-loop points.
• Write design docs, make build-vs-buy and model choices, and set success metrics for each workflow you own.
• Build Reliable AI in Production: Build production-grade LLM pipelines (prompt and context design, structured outputs, validation, fallbacks, confidence scoring).
• Integrate AI services cleanly with Jeeves's backend: clear API contracts, retries, graceful degradation, per-customer data isolation.
• Manage cost and latency across models, choosing the right model for each step.
• Measure, Monitor, and Improve: Build evaluation sets and automated evals for every workflow you own, and use them to catch regressions when prompts, models, or data change.
• Instrument AI components with logging, tracing, dashboards, and alerts so you know when quality drops before a customer does.
• Keep an audit trail of AI decisions that meets the standards of a regulated financial product.
• Raise the Bar for AI Engineering at Jeeves: Set patterns, shared tooling, and practices that other engineers can build on.
• Show the wider team how to use coding agents and AI tools well in day-to-day engineering.
• Review peers' AI system designs and share what you learn openly.

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).
• 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).
• Experience with observability for AI systems: logging, tracing, dashboards, and quality monitoring.
• Professional fluency in English, written and spoken.