Senior Backend Software Engineer, AI Observability & Evals Platform (SF)
LangChain is hiring a Senior Backend Software Engineer, AI Observability & Evals Platform (SF) in San Francisco, United States. It pays $180k-$240k a year and Level rates it ; you can apply on LangChain.
Level's read on this job
- Works on AI ●●●○ is how Level rates this software engineer role: the daily work is on AI products, without building the model.
- Pay on this posting starts 7% higher than the typical software engineer posting on Level.
- The posting mentions LangGraph, Clay and AI agents among its tools and skills.
- Level classes it as a senior role.
- LangChain has 103 other open roles on Level.
AI in this role
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. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale.
With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world.
Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater.
About The TeamThe LangSmith team owns and builds LangChain's core platform for observability, evaluation, and production reliability of AI systems. From tracing and annotation to run rules, evaluations, and beyond, this team owns LangSmith end-to-end. If you want to define what great AI observability looks like at production scale, this is where that work gets done.
About The RoleWe are looking for a Senior Backend Engineer to join us. In this role you will be 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.
What You'll DoDesign, 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.
5+ years of professional experience in backend engineering working on highly complex products
Proficiency in one or more 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
Annual salary range: $180,000- $240,000
Compensation Philosophy:
We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks.
We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.
BenefitsBenefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.
How we rate this
Senior Backend Software Engineer, AI Observability & Evals Platform (SF) at LangChain rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- This job starts at
- $180k
- Typical software engineer job
- $168k
This posting starts 7% above the typical software engineer job. See software engineer jobs
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Walk me through how you've used LangGraph in your day-to-day work.
- What are the limits of Clay that you've run into, and how did you work around them?
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: AI agents, LangGraph, and Clay. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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