Senior Software Engineer, Foundry IQ - CoreAI

Microsoft • Redmond, WA

1d • $119,800 - $261,000

About The Position

The Foundry IQ team is building agentic knowledge retrieval that combines enterprise knowledge with AI agents at scale. The team is expanding Azure AI Search to support complex queries involving refinement, reasoning, and reflection, with the goal of delivering high-quality, grounded results for people and large language models across varied industries, data volumes, and mission-critical scenarios.

In this role, you will design, build, and operate scalable Azure backend services and APIs that integrate with internal and external language models. You will work closely with Applied Science to turn research advances, prompts, models, and processing components into secure, reliable, scalable production capabilities. The work includes GPU-backed integrations for large-scale production machine-learning workloads, evaluation tooling for end-to-end AI quality, and advances in knowledge retrieval and data-layer AI integration such as RAG, agentic retrieval, and LLM context engineering. You will also determine where advanced reasoning models are valuable and integrate low-latency models where speed is critical.

You will work directly with customers and partner teams on challenging retrieval and AI problems, and collaborate with engineers, applied scientists, product leaders, and teams across Microsoft, including Bing, Fabric, Work IQ, and Microsoft Research. The role calls for distributed-systems experience and practical expertise in machine-learning infrastructure, GPU-hosted model integration, and LLM context engineering, along with the ability to navigate ambiguity and translate emerging AI capabilities into dependable, low-latency services at cloud scale.

Requirements

• Bachelor's degree in Computer Science or a related technical field and 4+ years of technical engineering experience coding in languages such as C, C++, C#, Java, JavaScript, or Python, or equivalent experience.
• Ability to meet Microsoft, customer, and/or government security screening requirements, including passing the Microsoft Cloud Background Check upon hire or transfer and every two years.
• Strong distributed-systems experience.
• Practical expertise in machine-learning infrastructure, GPU-hosted model integration, and LLM context engineering.
• Comfort partnering with Applied Science, handling ambiguous technical challenges, and translating emerging AI capabilities into secure, dependable, low-latency services at cloud scale.

Nice To Haves

• Development of Azure services with full understanding of service release and live-site responsibilities.
• Production-system coding experience in C# and Python.
• Ability to move quickly while ensuring quality at scale in a collaborative team setting.
• Development experience with large language models.
• Development experience with GPU-based models and model hosting.
• 2+ years of experience developing and deploying live production systems as part of a product team.
• Production-system coding experience in C++ or Java.
• Strong hybrid-work skills, including clear synchronous and asynchronous communication, teamwork, and collaboration.
• Customer-focused, strategic, results-driven, self-motivated, and action-oriented.
• Problem-solving ability, including solving problems that have not been solved before.

Responsibilities

• Design, build, and maintain Azure backend services and associated APIs.
• Partner with Applied Science to bring high-quality prompts, machine-learning models, and pre- and post-processing components into production securely, reliably, and at scale.
• Work directly with GPUs to support production machine-learning workloads at scale.
• Provide evaluation tooling and support production integrations to ensure end-to-end AI quality of Applied Science deliverables.
• Contribute to team plans, documents, and communications clearly and efficiently.
• Design, build, and operate scalable backend services that integrate with internal and external language models.
• Evaluate production systems for the quality, reliability, and performance of AI-powered experiences.
• Advance knowledge retrieval and data-layer AI integration, including RAG, agentic retrieval, and LLM context engineering.
• Work directly with customers and partner teams to solve challenging retrieval and AI problems.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior