Senior AI Engineer

Urban; Northern (KY); Hybrid; USD 180,000 - 260,000; Full time

Job summary

Jeeves is a remote-first, stablecoin-backed banking platform serving global enterprises. You will own AI workflows end to end, from design to deployment, working closely with Product and Backend teams to move fast without waiting for a spec.

This senior role requires shipping LLM-powered applications via APIs (OpenAI, Anthropic) and designing agentic, multi-step processes with human review where needed. You will implement robust monitoring, cost control, and data isolation for customers.

Qualifications

• 7+ years of professional software engineering experience.
• 2+ years building and operating LLM/AI-powered systems in production.
• Experience shipping LLM-powered applications via APIs such as OpenAI or Anthropic.
• Experience designing agentic or multi-step AI workflows (tool use, orchestration, human review steps).
• Strong proficiency in Python, plus REST APIs, PostgreSQL or similar relational DBs, 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.

Responsibilities

• Design agentic and LLM-based systems that combine extraction, retrieval, reasoning, and tool use.
• Write the design docs, make the build-vs-buy and model choices, and set success metrics for each workflow.
• Build production-grade LLM pipelines: prompt design, structured outputs, validation, fallbacks, and confidence scoring.
• Integrate AI services with Jeeves backend: API contracts, retries, degradation, and data isolation.
• Manage cost and latency across models, selecting the right model for each step.
• Build eval sets and automated evals to catch regressions when prompts or data change.
• Instrument components with logging, tracing, dashboards, and alerts.
• Keep an audit trail of AI decisions for regulated financial products.
• Set patterns and tooling that other engineers can reuse; share learnings.

Skills

LLM systems

Python

API integration

System ownership

Observability

English fluency

Backend fundamentals

Cloud provider

Tools

OpenAI API

Anthropic API

AWS

Job description

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. BMW, H&M, Lululemon, Burger King, Kavak and XP are among them, and more than 80% of customers use multiple Jeeves products.

We chose hard problems on purpose.

We hire for one thing: relentlessness. A strong motor that keeps going when the problem has no playbook. You'll know in your first week if Jeeves is right for you. For the right people, it's the steepest learning curve of your career.

Jeeves has raised more than $400 million in equity funding from Andreessen Horowitz, Y Combinator, CRV, Coinbase Ventures, GIC, AllianceBernstein, CoinFund and others.

If you want to rebuild how money moves across borders, come build it with us.

As an AI Engineer at Jeeves, you will own whole workflows from end to end, not individual features. You'll decide how to build it, ship it, measure it, and keep improving it. You'll work closely with Product, Backend Engineering, and our customers, but you won't wait for someone to hand you a spec.

This is a senior, hands-on role for people who are AI-native in how they work. You use coding agents and AI tools every day to move faster, and you know where they fall short. It isn't a research role, and it isn't a role for someone who wants a narrow, well-defined ticket queue.

Location: This role is remote based out of the United States. #LI-REMOTE

What You’ll Do:

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 the design docs, make the build-vs-buy and model choices, and set the 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, 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 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

Minimum 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