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Solutions Engineer (Chicago)

Langchain

LocationUnited States
Senioritysenior
CompanyLangchain
Verified recentlyChecked today
Compensation

Salary not listed

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Requirements and working style

Decision details from the source listing

Experience

6+ years stated

Benefits stated
medical coveragedental coveragevision coverageflexible vacation401(k) planmeals on in-office days (US)

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WFH.team analysis

What this posting tells you

Senior Solutions Engineer role at LangChain, remote with Chicago preferred location. Requires 6+ years in relevant technical roles with experience in cloud environments and AI agent production deployment. Full-time employment with standard US benefits. The role involves technical sales engineering for AI agent systems and collaboration with customer engineering teams.

Role lane

Customer success, DevOps, Healthcare admin, Marketing, Product, Sales, Security, Software

Where you can work

United States

Working hours

America/Chicago (Central Time)

Arrangement

senior · full_time

Required signals
solutions engineeringsales engineeringcustomer engineeringsoftware engineeringAI agentsPOC designtechnical discoveryarchitecture reviewscloud environmentsAWSGCPAzureKubernetes
Preferred signals
LangChainLangGraphLLM evaluationobservabilityguardrailscontainerization
Confirm before applying
  • Compensation is not listed
Market context

Customer success hiring on WFH.team

4,968active related roles
4,178new in the latest period
3105jobs per 100 candidates
$54kmedian of comparable listed ranges

Category counts come from WFH.team's latest published remote job market snapshot.

Explore the remote job market
Skills and signals
solutions engineeringsales engineeringcustomer engineeringsoftware engineeringAI agentsPOC designtechnical discoveryarchitecture reviewscloud environmentsAWSGCPAzureKubernetesLangChainLangGraphLLM evaluationRemote with Chicago, IL location specified
Job description

Solutions Engineer (Chicago) at Langchain

About us

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 TEAM

The Deployed Engineering team is the technical front line of our go-to-market motion. We partner with account executives from the first technical conversation through production rollout, helping companies evaluate LangChain, prove it out on their hardest use case, and get agents running reliably at scale.

This is a hands-on, highly technical team. Solutions Engineers own the technical win: scoping evaluations, designing POCs that mirror real workloads, answering the deep architecture questions that decide a deal, and staying with the customer after signature to make sure what we sold actually ships.

We sit at the intersection of engineering, product, and sales. What we learn in the field shapes both how customers adopt LangChain and what we build next.

About the role

You will work on some of the hardest problems in applied AI, in front of customers, on a clock. Not demos, not research: systems real teams depend on in production. The feedback loop is fast, the impact is measurable in closed deals and live deployments, and the work directly shapes how AI agents get built in the real world.

What you'll do

  • Own the technical win. Partner with AEs to scope evaluations, run technical discovery, and design POCs that map to the customer's real use case rather than a canned demo
  • Be the technical authority in the room during architecture reviews, security and infrastructure questions, and head-to-head evaluations
  • Co-architect and co-build production AI agents with customer engineering teams, from prototype through rollout
  • Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows
  • Run demos, trainings, and workshops for developer audiences, from single-team sessions to larger technical enablement
  • Advise customers post-sale on architecture, best practices, and roadmap-level decisions, and find the expansion opportunities that come out of those conversations
  • Surface field feedback to product and build reusable POC assets, cookbooks, and example code that scale across accounts
  • Contribute code upstream when it meaningfully improves customer outcomes

WHAT YOU'LL BRING

  • 6+ years in a relevant technical role such as solutions engineering, sales engineering, customer engineering, software engineering, or founding and product engineering, ideally at a startup or scale-up
  • Comfort owning the technical thread in a sales cycle: discovery, POCs, architecture reviews, and competitive evaluations
  • Ability to explain technical tradeoffs clearly and build trust with developer audiences, then translate that into a decision the customer is ready to make
  • A track record of taking responsibility for outcomes, not just recommendations
  • A bias toward action and a willingness to figure things out as you go
  • Genuine interest in operating AI agents in production, not just building demos

Nice to Haves

  • You've deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks
  • Experience carrying a technical number or working against pipeline alongside a sales team
  • Experience with LLM evaluation, observability, or guardrails
  • Experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts

Compensation

Annual OTE range: $200,000–$250,000 USD

Compensation Philosophy

We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.

Benefits

Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Company context

Working remotely at Langchain

Langchain is hiring for 5 active remote roles, with remote-friendly openings, application links, and job details refreshed from the public remote job inventory.

Headquarters
United States
Team size
51-200
Founded
2022
Remote policy

Remote hiring signal is inferred from active confirmed-remote job listings.

Application process

Review current openings on LangChain's official careers page before applying.

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