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Jeeves is a stablecoin-native banking platform for global enterprises, processing over $5B in annualized volume across 35 countries with payouts to 190 countries. The company serves major customers including BMW, H&M, Lululemon, Burger King, Kavak, and XP, with more than 80% of customers using multiple Jeeves products.
As a Senior AI Engineer, you will own complete AI workflows end to end—from design through launch and ongoing iteration. This is a hands-on role for engineers who are AI-native in their approach, using coding agents and AI tools daily to accelerate development.
Key responsibilities include:
**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**: Develop production-grade LLM pipelines with prompt and context design, structured outputs, validation, fallbacks, and confidence scoring. Integrate AI services cleanly with Jeeves's backend through clear API contracts, retries, graceful degradation, and per-customer data isolation. Manage cost and latency across models, selecting the right model for each step.
**Measure, Monitor, and Improve**: Build evaluation sets and automated evals for every workflow, catching regressions when prompts, models, or data change. Instrument AI components with logging, tracing, dashboards, and alerts. Maintain audit trails of AI decisions meeting regulated financial product standards.
**Raise the Bar for AI Engineering**: Set patterns, shared tooling, and practices for other engineers. Demonstrate effective use of coding agents and AI tools in day-to-day engineering. Review peers' AI system designs and share learnings openly.
This is not a research role and not for someone seeking narrow, well-defined tickets. You'll work closely with Product, Backend Engineering, and customers, but won't wait for someone to hand you a spec.
**Requirements:**
- 7+ years of professional software engineering experience, including at least 2 years building and operating LLM or AI-powered systems in production
- 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
