Backend Engineer, Observability & Evals Platform (LangSmith) at LangChain

Cambridge, Massachusetts, United States -

Full Time

Start Date

Immediate

Expiry Date

06 Jun, 26

Salary

190000.0

Posted On

08 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Backend Engineering, Python, Go, API Design, Data Services, High-Throughput Systems, Performance Tuning, Reliability, Postgres, Redis, Clickhouse, AWS, GCP, Azure, Testing, Monitoring

Industry

technology;Information and Internet

Description

About LangChain: At LangChain, our mission is to make intelligent agents ubiquitous. We provide the agent engineering platform and open source frameworks developers need to ship reliable agents fast. Our open source frameworks, LangChain and LangGraph, see over 90+ million downloads per month and help developers build agents with speed and granular control. LangSmith offers observability, evaluation, and deployment for rapid iteration, enabling teams to transform LLM systems into dependable production experiences. LangChain is trusted by millions of developers worldwide and powers AI teams at companies like Replit, Clay, Cloudflare, Harvey, Rippling, Vanta, Workday, and more. About the role: We are looking for a Backend Engineer to join our LangSmith team. In this role, you will be responsible for designing and building the backend systems that power LangChain’s observability and evals platform. You will work on the core services that allow developers to monitor and evaluate their AI applications at scale. While the focus is on backend feature development, familiarity with fullstack or frontend engineering, performance tuning, and debugging production issues would be extremely valuable. *This role is based in our San Francisco, New York, or Boston office. Employees within commuting distance work from the office five days per week. Candidates who live outside commuting distance (e.g. >1hr each way), may be eligible for hybrid arrangements depending on location and role requirements. What You Will Do: Design, develop, and maintain backend services and APIs to support LangSmith’s tracing, monitoring, and evaluation workflows. Collaborate on architectural decisions to ensure systems are performant and maintainable. Optimize storage and query performance for high-volume observability and evaluation data. Ensure system reliability through strong testing, monitoring, and alerting practices. Troubleshoot and resolve production issues, performing root-cause analysis and implementing long-term fixes. Create and maintain technical documentation, including system design and API references. Work closely with full-stack engineers, product managers, and product designers on rolling out new features. What You Will Bring: 2+ years of professional experience in backend engineering Proficiency in backend languages/frameworks, ideally Python or Go Strong understanding of API design and building reliable data services. Experience with high-throughput or mission-critical systems. Demonstrated ability to optimize backend services for performance and reliability. Experience with database systems (Postgres, Redis, Clickhouse), and cloud platforms (AWS, GCP, Azure) Strong communication skills, with the ability to collaborate cross-functionally Customer centricity and ownership mentality Compensation & Benefits: We offer competitive compensation that includes base salary, meaningful equity, and benefits such as health and dental coverage, flexible vacation, a 401(k) plan, and life insurance. Actual compensation will vary based on role, level, and location. For team members in the EU and UK, we provide locally competitive benefits aligned with regional norms and regulations. Annual salary range: $165,000- $190,000

Responsibilities

The engineer will design, develop, and maintain backend services and APIs crucial for LangSmith’s tracing, monitoring, and evaluation workflows, while collaborating on architectural decisions to ensure system performance and maintainability. Key tasks include optimizing storage and query performance for high-volume data and ensuring system reliability through robust testing and monitoring practices.