Software Engineering Manager, AI Observability & Evals Platform (Boston)
LangChain is hiring a Software Engineering Manager, AI Observability & Evals Platform (Boston) (United States). It pays $220k-$270k a year and Level rates it ; you can apply on LangChain.
Level's read on this job
- On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
- Tools and skills the posting cites include LangGraph, Clay and AI agents.
- Level lists 103 other open roles at LangChain.
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’re looking for an Engineering Manager to lead the team building LangSmith, our observability and evaluation platform for LLM applications. You’ll define the technical direction, grow and mentor a world-class engineering team, and partner with product and design to deliver features that help developers build and deploy trustworthy AI systems with confidence.
What you'll doBuild, mentor, and grow a high-performing team of engineers, fostering collaboration, ownership, and accountability
Strengthen LangChain’s engineering culture through mentorship, high-quality code, and technical excellence
Shape long-term technical direction and ensure scalability and reliability of LangSmith AI Observability Platform
Partner with product and design teams to define scope, sequence, and success criteria for key initiatives
Maintain a high bar for technical excellence while making sure the team moves with urgency and focus
Lead by example in writing clean, maintainable, and well-tested code in Go/Python and Typescript
Engage directly with customers to understand their needs and translate them into actionable product improvements
Experience managing or tech-leading teams delivering complex full-stack products
Strong technical background in Go/Python and React/Typescript
Solid understanding of databases (Postgres, Redis and ClickHouse)
Proven ability to design high throughput data-intensive systems
Bias towards shipping quickly and learning from customers
Strong communication skills—able to collaborate with internal stakeholders and engage directly with customers
Bonus: Experience building AI/LLM-powered applications, developer tools, or observability platforms
Annual salary range: $220,000- $270,000
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
Software Engineering Manager, AI Observability & Evals Platform (Boston) at LangChain rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● 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
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?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
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.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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