# Deployed Engineer (Raleigh)

**Company:** [LangChain](https://hotfix.jobs/companies/langchain)
**Location:** Remote
**Role:** Solutions Architecture
**Salary:** $150k – $250k/yr
**Experience:** 3+ years
**Skills:** Python, JavaScript, LangChain, LangGraph, LLMs, AWS, GCP, Azure, Kubernetes, llm evaluation, Observability, guardrails
**Posted:** 2026-04-14

> Deployed Engineer partners with customer teams to co-build, deploy, and operate production AI agents using LangChain/LangGraph. Owns technical wins in pre-sales POCs/evaluations and provides post-sale architecture advice, demos, and best practices. Requires 3+ years technical experience, strong Python/JS, and hands-on agent design beyond basic APIs.

## Job Description

## Responsibilities
- Co-architect and co-build production AI agents with customer engineering teams.
- Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations.
- Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows.
- Advise customers post-sale on architecture, best practices, and roadmap-level decisions.
- Run technical demos, trainings, and workshops for developer audiences.
- Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers.
- Occasionally contribute code upstream when it meaningfully improves customer outcomes.

## Requirements
- 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up.
- Strong Python, JavaScript and systems fundamentals.
- Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling.
- Comfortable working directly with customers during POCs, architecture reviews, and technical evaluations.
- Can explain technical tradeoffs clearly and build trust with developer audiences.
- Take responsibility for outcomes, not just recommendations.
- Bias toward action and enjoy figuring things out as you go.
- Excited about operating AI agents in production, not just building demos.

## Nice-to-Haves
- Deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks.
- Worked with LLM evaluation, observability, or guardrails.
- Experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts.
- Shipped and operated production software and comfortable owning systems under real-world constraints.

## Compensation
- Annual OTE range: $150,000–$250,000 USD.
- Competitive compensation that includes base salary, variable compensation, meaningful equity, benefits, and perks. Actual compensation varies based on role, level, and location.
- Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

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