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Jeeves is a stablecoin-native banking platform serving global enterprises. The company processes over $5B in annualized volume, serves thousands of customers across 35 countries, and has raised over $400M from top-tier investors including Andreessen Horowitz, Y Combinator, and Coinbase Ventures.
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 and use coding agents and AI tools daily to move faster.
Key responsibilities:
**Own AI Workflows End to End**
- Design agentic and LLM-based systems combining 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
**Build Reliable AI in Production**
- Build production-grade LLM pipelines with prompt and context design, structured outputs, validation, fallbacks, and confidence scoring
- Integrate AI services cleanly with Jeeves's backend: clear API contracts, retries, graceful degradation, and 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, catching regressions when prompts, models, or data change
- Instrument AI components with logging, tracing, dashboards, and alerts to detect quality drops before customers do
- 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 wanting a narrow, well-defined ticket queue. 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 using 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
