Ai Engineer Jobs

About The Position

Requirements

• Bachelor’s degree in Computer Science or a related technical field and at least 4 years of technical engineering experience coding in languages such as C, C++, C#, Java, JavaScript, or Python, or equivalent experience.
• Growth mindset, resilience, and communication and collaboration skills.

Nice To Haves

• Bachelor’s or master’s degree in Computer Science, Engineering, or a related technical field and at least 4 years of technical engineering experience, or a Ph.D. and at least 3 years of experience.
• At least 4 years of professional software development experience with languages such as Python, TypeScript/JavaScript, C, C++, or C#.
• At least 2 years of experience training, fine-tuning, and evaluating ML/LLM models, including data preparation, experiment design, offline and online validation, and performance optimization.
• At least 2 years of production experience architecting and deploying applications with LLMs and/or agent systems.
• Coursework, research, or relevant training in ML, AI, or LLMs, with a demonstrated record of working in interdisciplinary areas spanning applied science, engineering, and product.
• Technical leadership experience, including orchestrating production agentic systems, prompt design, tool or function calling, context and memory management, routing or planning, and evaluation.
• Deep understanding of asynchronous programming patterns, microservices architecture, and event-driven systems.
• Experience in a professional domain such as finance, accounting, or human resources, including understanding domain-specific workflows, business rules, and customer needs.
• Experience in forward-deployed engineering or a similar customer-facing technical role, partnering directly with customers to build secure and scalable systems, operate deployed solutions, and improve them using production feedback.

Responsibilities

• Architect, prototype, and iteratively develop AI agent experiences that reimagine domain-specific workflows across Copilot in Office and Copilot Cowork; validate feasibility, user experience, and technical approaches.
• Deliver features at the intersection of software engineering, applied science, product, and domain expertise by translating customer needs, domain knowledge, model capabilities, and product intent into production-ready systems.
• Design evaluation frameworks and observability tools to monitor agent health, investigate customer feedback, and build continuous-learning systems for end-to-end AI workflows.
• Work directly with customers and domain experts to understand complex workflows, explore interaction paradigms, and build system architectures that support collaboration between people and AI.
• Identify and drive improvements to agent development platforms, engineering and domain knowledge bases, build processes, and engineering standards.
• Mentor coworkers and promote technical excellence and continuous learning.
• Embody Microsoft culture and values.