# Deployed Engineer (Southeast)

**Company:** [LangChain](https://hotfix.jobs/companies/langchain)
**Location:** Charlotte, NC, Raleigh, NC, Atlanta, GA
**Role:** ML Engineering
**Salary:** $150k – $250k/yr
**Experience:** 3+ years
**Skills:** Python, JavaScript, LangChain, LangGraph, LLMs, AI Agents, Kubernetes, AWS, GCP, Azure
**Posted:** 2026-03-12

> Deployed Engineer co-architects and builds production AI agents with customers, owns technical wins in pre-sales, and advises on deployment and operations. Requires 3+ years experience, strong Python/JavaScript, and expertise in agent-based LLM applications.

## Job Description

## What You’ll Do
- 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

## What You’ll Bring
- **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
- Are 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
- Have a **bias toward action** and enjoy figuring things out as you go
- Are excited about **operating AI agents in production**, not just building demos

## Nice to Have’s
- You’ve deployed **AI agents in production**, especially using **LangChain, LangGraph**, or similar frameworks
- Worked with **LLM evaluation, observability, or guardrails**
- Have experience with **cloud environments** (AWS, GCP, Azure), containers, and basic Kubernetes concepts
- Have **shipped and operated production software** and are comfortable owning systems under real-world constraints

## Compensation & Benefits
**Annual OTE range: $150,000–$250,000 USD**

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