Applied AI Engineer, Enterprise

OpenAI
São Paulo
Workplace: HybridFull timeFunction: Data Science & Machine LearningSkills: ["Communication","Technical judgment","End-to-end ownership","Collaboration","High agency"]

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.

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FursaFursa
OpenAI
OpenAI
1 month ago

Applied AI Engineer, Enterprise

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Source: Company careers pageValidated by: Fursa AI
Last checked: 55 minutes 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
Glassdoor: 4.4
WebsiteLinkedInGlassdoor