# AI Deployment Engineer, Enterprise

**Company:** [OpenAI](https://hotfix.jobs/companies/openai)
**Location:** San Francisco, CA, New York, NY
**Role:** Solutions Architecture
**Salary:** $197k – $278k/yr
**Experience:** 5+ years
**Skills:** Python, Ai Systems, Machine Learning, Evaluation Harnesses, Integrations, Reliability, Observability, Security, Data Governance, Retrieval, Agents, LLMs
**Posted:** 2026-07-08

> Partner with enterprise customers to design, build, and deploy production AI systems from prototype to scaled impact. Requires hands-on Python proficiency, AI/ML deployment experience, and strong technical judgment across reliability, security, and governance.

## Job Description

## Responsibilities
- Partner directly with enterprise customers to identify high-value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteria.
- Design, build, and deploy AI systems that solve important customer problems and produce measurable business outcomes.
- Work hands-on in code to build prototypes, evaluation harnesses, reference implementations, integrations, and production accelerators.
- Make sound technical decisions across models, agents, retrieval, tools, data, reliability, observability, latency, cost, safety, security, and governance.
- Diagnose complex implementation challenges, reproduce failures, test hypotheses, and drive blockers toward resolution.
- Help customers progress from promising prototypes to reliable production systems, sustained adoption, and scaled impact.
- Partner closely with customer engineering teams and OpenAI Product, Research, Engineering, Security, and go-to-market teams, translating deployment experience into high-signal product feedback.
- Create reusable architectures, tooling, playbooks, and technical guidance that accelerate future enterprise deployments.

## Requirements
- Demonstrated track record of designing, building, and delivering AI or machine-learning systems in enterprise environments, including taking systems from prototype to production. Relevant backgrounds may include applied AI or ML engineering, forward-deployed engineering, software engineering, customer engineering, solutions architecture, or technical consulting.
- Substantial personal contributions in code, architecture, evaluation, debugging, or production engineering.
- Highly proficient in Python and comfortable working across an AI application stack.
- Understand how to evaluate AI systems systematically using representative data, graders, production signals, and human judgment.
- Experience navigating enterprise production requirements such as integrations, reliability, observability, security, privacy, data governance, performance, and cost.
- Ability to connect technical decisions to customer workflows, adoption, and measurable business outcomes.
- Communicate with clarity and credibility across hands-on engineers, technical leaders, security teams, product leaders, and executives.
- High agency, strong technical judgment, and end-to-end ownership in ambiguous environments.
- Learn quickly, challenge assumptions constructively, and collaborate with humility.

## Nice-to-Haves
- Experience with JavaScript, TypeScript, or another relevant language.
- Experience in a particular industry or with OpenAI products.

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