Join Microsoft Digital (MSD) and shape the future of AI-powered developer productivity. We are building the next generation of agentic platforms, integrating cutting-edge AI models to enhance how developers work. This is an opportunity to innovate, influence, and grow within a dynamic and forward-thinking organization.

Our team operates at the forefront of AI systems, focusing on the full lifecycle of agentic solutions. We design core capabilities that influence agent behavior, including tool integration, planning, orchestration, evaluation, and safety features. We also build the foundational AI components that ensure dependability, such as observability, progressive delivery, and reliability engineering. Furthermore, we prioritize creating seamless and intuitive user experiences for our AI agents across all devices.

As a Senior Software Engineer, you will harness modern AI-assisted development practices to boost delivery speed while upholding stringent code quality. You'll actively use AI in your daily coding, championing its evolution within the team and to our customers. Embrace experimentation with diverse AI approaches, even those yet to be fully explored.

Provide impactful mentorship and coaching to fellow engineers, both within and beyond your immediate team. Develop innovative AI-powered product features leveraging technologies like large language models (LLMs), vector stores, and agentic workflows to enhance security analysis and customer outcomes. Drive continuous improvements in engineering efficiency through AI tooling, automation, and comprehensive documentation.

Take full ownership of medium-to-large features from conception through deployment and ongoing iteration in production. Utilize programming languages such as TypeScript, JavaScript, and React. Design, develop, and maintain robust backend services and APIs critical for agentic workflows and platform capabilities. Collaborate closely with Product Management, Design, and partner teams to architect scalable solutions. Lead by example, championing best engineering practices, elevating code quality, and refining the team's incident response.

Explore and evaluate various design options for product features, articulating their respective strengths and weaknesses. Apply AI tools and practices diligently throughout the Software Development Lifecycle (SDLC). Integrate Security-by-Design and Responsible AI principles, particularly when building features that leverage AI for threat detection and response. Foster a positive team culture characterized by a growth mindset, receptiveness to feedback, and collaborative spirit within a fast-paced, data-driven environment.

We require a Bachelor's Degree in Computer Science or a related technical field, coupled with 4+ years of technical engineering experience involving coding in languages like C, C++, C#, Java, JavaScript, or Python, or equivalent practical experience. Direct experience building and managing LLM-powered agentic systems in production, with accountability for quality, reliability, and iterative improvements, is essential.

Demonstrate proficiency in building production software using modern programming languages, with a focus on AI LLMs, agents, skills, C#, Java, or Python. Showcase expertise in AI-assisted software development tools and workflows, such as AI coding agents and LLM-powered development environments. A strong understanding of LLM and Generative AI application development is crucial.

Familiarity with AI pair programming tools like GitHub Copilot and Copilot Workspace, as well as prior experience with agentic plugins, agents, skills, and hooks, is expected. Experience building with Agent SDKs, large language models (LLMs), prompt engineering, or AI orchestration frameworks is highly valued. Understanding of agentic AI development patterns, including multi-step reasoning, tool/function calling, retrieval-augmented generation (RAG), and human-in-the-loop workflows, is beneficial.

Possess a strong product mindset with a proven ability to navigate and resolve ambiguous problem spaces, driving them to high-quality outcomes. Exhibit solid engineering fundamentals, encompassing systems design, performance optimization, and debugging within complex production environments. Showcase a track record of designing, implementing, and refining evaluations for agentic systems, covering tools, prompts, and agent loops. A good grasp of Generative AI and software engineering fundamentals, data structures, and problem-solving skills is necessary.