OpenAI

1 day ago

AI Deployment Engineer, Enterprise

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Partner with enterprise customers to design, build, and deploy AI systems that deliver measurable business outcomes. Use hands-on engineering—coding, debugging, building evaluation harnesses, and resolving integrations—to progress solutions from prototype to reliable production. Make technical decisions across models, agents, retrieval, tools, data, reliability, observability, latency, cost, and safety. Translate deployment learnings into reusable architectures and high-signal product feedback.

Location: São Paulo

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key 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 by reproducing failures, testing hypotheses, and driving blockers toward resolution.

Key Requirements

•Demonstrated track record designing, building, and delivering AI or machine-learning systems in enterprise environments, taking systems from prototype to production.
•Substantial personal contributions in code, architecture, evaluation, debugging, or production engineering—not just stakeholder management.
•Highly proficient in Python and comfortable working across an AI application stack; experience with JavaScript or TypeScript is valuable.
•Ability to evaluate AI systems systematically using representative data, graders, production signals, and human judgment.
•Experience navigating enterprise production requirements including integrations, reliability, observability, security, privacy, data governance, performance, and cost.

Experience:AIMachine learningEnterprise environments

Skills:CommunicationTechnical judgmentEnd-to-end ownershipCollaborationHigh agency

Tech Stack:PythonJavaScriptTypeScript

Company Brief

OpenAI

Develops and deploys advanced generative AI models (including ChatGPT and DALL·E) and AI infrastructure, providing APIs and consumer products to accelerate safe AGI for broad benefit.

Industry: AI & Machine Learning

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Scaleup

Valuation: Hectocorn (USD 100B+)

Funding: Series E+

Headquarters: San Francisco, United States

Founded: 2015

Glassdoor: 4.4

Website LinkedIn Glassdoor

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OpenAI

1 day ago

AI Deployment Engineer, Enterprise

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: São Paulo

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key 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 by reproducing failures, testing hypotheses, and driving blockers toward resolution.

Key Requirements

•Demonstrated track record designing, building, and delivering AI or machine-learning systems in enterprise environments, taking systems from prototype to production.
•Substantial personal contributions in code, architecture, evaluation, debugging, or production engineering—not just stakeholder management.
•Highly proficient in Python and comfortable working across an AI application stack; experience with JavaScript or TypeScript is valuable.
•Ability to evaluate AI systems systematically using representative data, graders, production signals, and human judgment.
•Experience navigating enterprise production requirements including integrations, reliability, observability, security, privacy, data governance, performance, and cost.

Experience:AIMachine learningEnterprise environments

Skills:CommunicationTechnical judgmentEnd-to-end ownershipCollaborationHigh agency

Tech Stack:PythonJavaScriptTypeScript

Company Brief

OpenAI

Develops and deploys advanced generative AI models (including ChatGPT and DALL·E) and AI infrastructure, providing APIs and consumer products to accelerate safe AGI for broad benefit.

Industry: AI & Machine Learning

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Scaleup

Valuation: Hectocorn (USD 100B+)

Funding: Series E+

Headquarters: San Francisco, United States

Founded: 2015

Glassdoor: 4.4

Website LinkedIn Glassdoor