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Senior AI Agent Engineer

Role overview

Qualifications

  • 5+ years in software engineering, developer tooling, or platform engineering
  • Production experience with LLM agents: tool use, retrieval, structured outputs, orchestration
  • Strong TypeScript or Python and experience building API integrations
  • Strong written communication; you can turn an expert's workflow into a precise spec

Responsibilities

  • Own and improve the agent
  • Build knowledge systems that help agents find, connect, and reason over Relay's structured and unstructured information
  • Integrate agents with internal systems through APIs and MCP tools
  • Measure task success, correction rate, latency, and cost, and report them

Key facts

  • Remote from: United States
  • Full time
  • Senior (5-10 years)
  • AI Engineer
  • English

Hard skills

Other skills

  • Communication
  • Problem Solving

About the company

Relay logo

Relay

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Company details

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Job description

About us

Relay is a cross-chain payments protocol that provides instant, low-cost cross-chain bridging, swaps, and transactions. We're the fastest and cheapest way to bridge and transact across chains, serving over 5 million users who have completed 59+ million transactions with $6+ billion in volume across 85+ chains.

Our company mission is to make transacting across chains as fast, cheap, and reliable as online payments. We are building the core infrastructure to abstract chains from end user payments, enabling the next billion users to experience the benefits of blockchain without the UX burdens.

About the role

We're hiring a Senior AI Agent Engineer on the Developer Experience team. You'll own Relay's internal AI agent — a Slack-native agent that works across our tools to investigate issues, answer questions, and complete operational work.

This is a hands-on builder role. You're measured by what the agent gets done, accurately and safely.

What you'll do

Cover US business hours

  • This role is remote within the United States, with dependable overlap with the teams whose workflows you're automating.

Own and improve the agent

  • Own the agent backlog; prioritize by impact, frequency, and risk

  • Review real misses each week and turn them into regression evals, fixed tools, or better guidance

  • Turn expert workflows into agent skills, decision logic, and escalation paths

  • Build knowledge systems that help agents find, connect, and reason over Relay's structured and unstructured information, with clear provenance and freshness

  • Improve retrieval, orchestration, and verification; own regressions through resolution

  • Measure task success, correction rate, latency, and cost, and report them

Connect agents to Relay's systems safely

  • Integrate agents with internal systems through APIs and MCP tools

  • Choose deterministic code, simple automation, or agent behavior on the merits

  • Treat permissions, side effects, human approval, and failure recovery as product features

About you

  • You're a product-minded engineer who ships AI systems into real workflows

  • You care about correctness, permissions, and failure handling as much as model capability

  • You read traces before you change prompts

  • You'd often rather add a linter, a type, or a test than tune a prompt

  • You know when conventional software beats an agent

  • You can sit with a domain expert, extract how they decide, and encode it into testable behavior

  • You're comfortable being the first dedicated hire for a new function

Skills and abilities

Must-have

  • 5+ years in software engineering, developer tooling, or platform engineering

  • Production experience with LLM agents: tool use, retrieval, structured outputs, orchestration

  • Experience building search, retrieval, or knowledge systems across structured and unstructured information

  • Strong TypeScript or Python and experience building API integrations

  • Experience designing evals or automated tests for nondeterministic software

  • Familiarity with permissions, secrets, auditability, and safe handling of side effects

  • Strong written communication; you can turn an expert's workflow into a precise spec

Nice to have

  • Experience with MCP or comparable tool and context protocols

  • Experience with Slack apps, support automation, or internal platforms

  • Experience with entity resolution, knowledge graphs, ontology or taxonomy design, ranking, or semantic enrichment

  • Experience in crypto, payments, or another high-stakes domain

What we offer

  • Competitive base salary

  • Equity package

  • Comprehensive health benefits

  • Unlimited PTO policy with encouraged minimum

  • Remote-first culture with emphasis on collaboration, communication, and flexibility

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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