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Software Engineer Foundry Agent

United States, Redmond Employment contract 84200.00 - 165200.00 USD / Year · Job Posted May 04, 2026
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Job Description

Do you want to fine-tune OpenAI’s most advanced models on Azure — working with GPT-4.1, GPT-5, and beyond? From supervised fine-tuning (SFT) to reinforcement learning methods like DPO and others, this role puts you hands-on with the techniques shaping the future of AI. On this team, you’ll play a key role in improving the performance and reliability of customizing some of the world’s most advanced AI models. You’ll gain experience with fine-tuning workflows, experimenting with reinforcement learning techniques, and applying advanced optimization strategies that directly impact product quality. You’ll also work directly with the training code, debug complex behaviors, and sharpen the skills that make cutting-edge models more reliable and effective. The models you help shape will power critical workloads at some of the world’s leading companies. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. This role is targeting an immediate start date.

Job Responsibility

  • Creates and implements code for a product, service, or feature, reusing code as applicable with minimal supervision
  • Writes and learns to create code that is extensible and maintainable
  • Considers diagnosability, reliability, and maintainability with few defects, and understands when the code is ready to be shared and delivered
  • Reviews product feature code and test code to ensure it meets team standards, contains the correct test coverage, and is appropriate for the product feature
  • Supports efforts to use debugging, tests, tools, logs, telemetry, and other methods to proactively verify assumptions before issues occur for product features in production
  • Contributes to the identification of requirements for, and development of automation within production and deployment of a complex product feature, targeting zero-touch deployment when possible
  • Runs code in simulated, or other non-production environments to confirm functionality and error-free runtime for products with little to no oversight
  • Applies best practices to build code based on well-established methods and secure design principles while also applying best practices for new code development and formal validation of security invariants
  • Follows best practices for product development and scaling to customer requirements, and applies best practices for meeting scaling needs and performance expectations and security promises

Requirements

  • Bachelor's Degree in Computer Science, or related technical discipline with proven experience coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • OR equivalent experience
  • Ability to meet Microsoft, customer and/or government security screening requirements
  • Microsoft Cloud Background Check

Nice to have

  • Master's Degree in Computer Science or related technical field with proven experience coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • OR Bachelor's Degree in Computer Science or related technical field AND 1+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • OR equivalent experience
  • Dependable knowledge and practical usage of modern AI-assisted engineering tools—such as GitHub Copilot (including Copilot Chat), Visual Studio, VSCode, Microsoft Copilot, Azure AI Studio, and LLM tools—to support tasks like prototyping, debugging, test generation, documentation, and code review, paired with a strong ability to validate outputs and protect sensitive data
  • Reliable knowledge of machine learning systems and data pipelines

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