Agent Reliability Engineer, GTM
ABOUT THE TEAM:
GTM Engineering builds the AI agents, systems, and automation that power how our go-to-market teams work. We partner across Sales, Marketing, Customer Success, Support, and other GTM functions to identify high-leverage problems and build solutions that improve speed, quality, and scale. Our work spans four core areas:
- Identify — find high-leverage GTM workflows where AI can meaningfully improve how we operate
- Build — design, build, and deploy production AI agents and automated workflows across GTM
- Enable — drive adoption through thoughtful rollouts, playbooks, best practices, and ongoing enablement
- Evangelize — share what we build and learn externally through content, demos, talks, and open source examples
ABOUT THE ROLE:
You'll own the health, cost, performance, and business impact of the GTM Agent, and build the feedback loops that keep it improving. Because we build the platform we run on, you'll also operate the agent on LangSmith the way we tell customers to, and turn that practice into the reference story enterprises keep asking us for. You'll work across Python 3.11, FastAPI, LangGraph, DeepAgents, LangSmith, Supabase Postgres, BigQuery, Anthropic and OpenAI models, and Slack and Next.js surfaces.
WHAT YOU'LL DO:
- Monitor production health across every graph, catching errors, slow runs, expensive runs, and silent failures before reps report them
- Triage incoming issues from Slack, tickets, and rep reports, fixing small things directly and routing the rest to the right owner
- Run the weekly eval suite, investigate failures, and turn real production bugs into permanent regression tests
- Track cost and latency by model, graph, use case, and role, and recommend concrete changes to model choice, reasoning effort, and caching
- Track usage and adoption per rep and per feature, and own the weekly health report the team runs on
- Build the business metrics that show leadership what the agent is worth, from reply rates and meetings booked to hours reclaimed and ROI
- Build our own monitoring and alerting on LangSmith, and write the “how we run our own agent” story for customers
WHAT YOU'LL BRING:
- Strong production Python and SQL, comfortable working in traces, logs, and warehouse tables
- Real experience running LLM applications, including tracing, evals, and prompt and cache mechanics
- SRE or production operations instincts: percentiles, SLOs, and separating noise from real pattern
- Healthy skepticism about metrics; you check what a number actually counts before you publish it
- Clear writing, and interest in publishing what you learn
- High agency; you notice what's missing and take initiative to build it
NICE TO HAVES:
- LangGraph or LangSmith experience
- Experience building an eval suite from scratch
- BigQuery or dbt
- Prior DevRel-adjacent writing
- Empathy for sales and go-to-market users
Salary: $150,000 - $190,000