Base Salary
$150k - $190k/yr
Responsibilities
- Monitor production health across agent graphs and identify errors, slow runs, expensive runs, and silent failures.
- Triage issues from Slack, tickets, and go-to-market representatives, resolving smaller issues and routing others to the appropriate owner.
- Run weekly evaluation suites, investigate failures, and convert production bugs into permanent regression tests.
- Track cost and latency by model, graph, use case, and role, and recommend changes to model selection, reasoning effort, and caching.
- Track usage and adoption by representative and feature, and own the team’s weekly health report.
- Build business metrics covering reply rates, meetings booked, hours reclaimed, and return on investment.
- Build monitoring and alerting on LangSmith and document how LangChain operates its own agent for customers.
Requirements
- Strong production Python and SQL skills, with comfort working in traces, logs, and warehouse tables.
- Hands-on experience running LLM applications, including tracing, evaluations, prompt mechanics, and cache mechanics.
- SRE or production operations instincts, including understanding percentiles and service-level objectives and distinguishing noise from meaningful patterns.
- Ability to scrutinize metrics and verify what measurements actually count before publishing them.
- Clear writing skills and interest in publishing technical learnings.
- High agency and initiative to identify gaps and build solutions.
Benefits
- Medical, dental, and vision coverage.
- Flexible vacation.
- 401(k) plan.
- Meals on in-office days in the US.
- Compensation includes base salary, variable compensation for relevant roles, equity, benefits, and perks; offerings vary by role, level, and location.
- Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.
Categories
About LangChain
At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. What began as widely adopted open-source tools has grown into a platform for building, evaluating, deploying, and operating agents at scale. LangChain provides the agent engineering platform and open source frameworks developers need to ship reliable agents fast. LangSmith offers observability, evaluation, and deployment for rapid iteration. Our open source frameworks, LangGraph, LangChain, and Deep Agents, help developers build agents with speed and granular control. LangSmith is trusted by leading AI teams at Zip, Vanta, Klarna, Workday, Linkedin, Cloudflare, and more.