# AI Product Engineer

**Company:** [Camber](https://hotfix.jobs/companies/camber)
**Location:** New York, NY
**Role:** Fullstack Engineering
**Salary:** $190k – $230k/yr
**Experience:** 3+ years
**Skills:** Python, LLMs, APIs, Data Pipelines, AWS, LangGraph, Temporal, Arize Phoenix, Promptfoo, Openinference
**Posted:** 2026-03-31

> Builds and ships AI-powered products and tools integrating LLMs into workflows, owning end-to-end from prototype to production. Requires 3+ years backend/full-stack experience with strong Python skills and autonomous problem-solving in a fast-paced environment.

## Job Description

## What you'll do
- Rapidly prototype and ship AI-powered solutions to validate ideas and drive real impact
- Own problems end-to-end from ambiguous idea to production system with minimal oversight
- Build AI-powered products and tools that automate workflows, support decision making, and improve internal and customer-facing experiences
- Operate across the stack including **backend services**, **APIs**, **data pipelines**, and lightweight product surfaces
- Integrate AI capabilities such as **LLMs** into real workflows, ensuring they are reliable, observable, and cost-efficient
- Run fast feedback loops by testing, measuring, and iterating using evaluation frameworks and real usage data
- Develop reusable patterns and tooling that enable faster experimentation and iteration across the team

## What we're looking for
**Experience:**
- **3+ years** of experience building production systems as a backend or full-stack engineer
- Strong **Python** proficiency: comfortable building production systems and data workflows in **Python**
- Highly autonomous: able to take loosely defined problems and independently drive them to outcomes
- Strong experimentation and analytical approach: able to design experiments, construct evaluation frameworks using historical data, and iterate quickly based on results
- Generalist builder: comfortable working across product engineering, data, and infrastructure, with a focus on shipping practical solutions rather than research or theory
- Customer and product intuition: able to understand workflows and pain points to build useful systems
- Curiosity: motivated to learn new tools, frameworks, and domains quickly, especially in a fast-evolving AI landscape

**Nice to have:**
- Experience integrating **LLMs** or AI capabilities into production systems
- Familiarity with evaluation tools such as **Arize Phoenix** or **Promptfoo**
- Experience building agent-based workflows using frameworks like **LangGraph**
- Familiarity with orchestration tools such as **Temporal**
- Exposure to AI observability and tracing standards such as **OpenInference**
- Familiarity with cloud platforms such as **AWS**

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**Canonical:** https://hotfix.jobs/jobs/7deca395-dd51-4df4-9a35-a25551de2e74