Senior Applied AI Engineer

Microsoft•Redmond, WA

22h

About The Position

Microsoft is seeking a Senior Applied AI Engineer to join a pioneering team focused on building the future of automated business workflows through Agentic AI systems and Digital Collaborators. This role is part of the Software Engineering discipline and combines strong engineering fundamentals with deep applied AI expertise. You will work at the intersection of generative AI, large language models (LLMs), and Conversational and autonomous agent architectures, building intelligent systems capable of reasoning, planning, and executing complex, multi-step tasks across enterprise environments. As part of the Microsoft Dynamics organization, you will help shape the next generation of intelligent assistants and digital collaborators that deliver real business outcomes at scale. You will take applied AI solutions from experimentation through production deployment, influencing system architecture, product direction, and customer experience. You’ll be part of an inclusive, customer-driven team that values growth mindset, collaboration, and continuous learning. Our team is passionate about building AI solutions that empower users and transform industries. We operate at the forefront of AI innovation, with a strong sense of ownership, creativity, and purpose. 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.

Requirements

Bachelor's Degree in Computer Science, Engineering, Data Science, Math, Business, or related field AND 4+ years experience in engineering, product/technical program management, data analysis, or product development OR equivalent experience.
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Nice To Haves

8+ years of professional software development experience with at least one of the following: C#, C++, or Java.
8+ years of professional experience building cloud applications, preferably full stack.
3+ years of experience with GenAI, LLMs, or agentic systems.
Experience designing and implementing enterprise-scale services.
Experience delivering Dynamics 365 and/or Power Platform solutions is desirable.
Experience in agentic AI development and leveraging AI tools for development.
Verbal, written, and cross-team collaboration skills.
Team player and collaborator across time zones and diverse stakeholder groups.
Passion for improving software quality and engineering excellence.
Experience developing, debugging, and supporting code in object-oriented languages, as well as writing database queries.
Experience building infrastructure using Microsoft Azure technologies such as Service Fabric, App Service, and Docker.

Responsibilities

Design, build, and ship AI-powered software systems leveraging generative AI, LLMs, and agentic reasoning frameworks.
Develop and integrate autonomous AI agents capable of task decomposition, multi-step planning, memory, tool usage, and dynamic decision-making across enterprise workflows.
Apply state-of-the-art techniques including foundation models, prompt engineering, retrieval-augmented generation (RAG), multi-agent architectures, and classical machine learning where appropriate.
Fine-tune and adapt foundation models using domain-specific data, and evaluate model behavior across relevance, quality, hallucination, bias, latency, and cost.
Build rapid prototypes and translate them into production-grade systems, contributing to deployment, debugging, monitoring, and operational excellence.
Design and implement evaluation frameworks and automated evaluators, using offline experiments, shadow testing, online experimentation, and telemetry to measure impact and guide iteration.
Partner closely with product managers, researchers, and engineers to bring agentic capabilities into Microsoft’s business and productivity platforms.
Write high-quality, well-documented, and maintainable code, along with clear technical design specifications.
Mentor engineers and contribute to raising the overall engineering and applied AI bar across the team.
Apply Responsible AI principles throughout the development lifecycle, proactively identifying and mitigating risks related to fairness, bias, privacy, security, and misuse.