Solutions Engineer (Texas)
About The Position
LangChain is seeking a Solutions Engineer to join their Deployed Engineering team. This role is the technical front line of the go-to-market strategy, partnering with account executives from initial technical conversations through production rollout. The Solutions Engineer will help companies evaluate LangChain, prove its capabilities on challenging use cases, and ensure AI agents run reliably at scale. This is a hands-on, highly technical position focused on owning the technical win by scoping evaluations, designing Proofs of Concept (POCs) that mirror real workloads, addressing complex architectural questions, and supporting customers post-signature to ensure successful product shipment. The role operates at the intersection of engineering, product, and sales, with insights from the field directly influencing product development and customer adoption. The Solutions Engineer will work on challenging applied AI problems in a production environment, with a fast feedback loop and measurable impact on closed deals and live deployments, directly shaping the future of AI agent development.
Requirements
- 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 clearly explain technical tradeoffs and build trust with developer audiences, translating this into customer decisions.
- 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
- Experience deploying 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.
Responsibilities
- Own the technical win by partnering 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.
- Serve as the technical authority during architecture reviews, security and infrastructure discussions, and competitive evaluations.
- Co-architect and co-build production AI agents with customer engineering teams, from prototype through rollout.
- Assist customers in deploying and operating agent-based applications, including conversational agents, research agents, and multi-step workflows.
- Conduct demos, trainings, and workshops for developer audiences, ranging from single-team sessions to larger technical enablement events.
- Advise customers post-sale on architecture, best practices, and roadmap decisions, identifying expansion opportunities.
- Surface field feedback to the product team and develop reusable POC assets, cookbooks, and example code to scale across accounts.
- Contribute code upstream when it significantly improves customer outcomes.
Benefits
- Medical, dental, and vision coverage
- Flexible vacation
- 401(k) plan
- Meals on in-office days in the US
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
