Principal Applied AI Engineer

The Principal Applied AI Engineer role is a hands-on technical architecture position focused on building production agentic AI services for Azure customer support at scale. You will own end-to-end technical delivery, including evaluation, security, reliability, and measurable impact for AI-first resolution systems.

Location

Redmond, WA (onsite)

Salary

USD 142,800 - 304,200 per yearly

Software Engineering IC5 typical base pay range across the U.S.: USD $142,800 - $274,800 per year.

A different range applies to specific work locations, including the San Francisco Bay Area and New York City Metroplit: USD $188,000 - $304,200 per year.

Responsibilities

• Architect and build production agentic AI systems, including LLM orchestration, multi-agent workflows, RAG pipelines, tool integrations, memory and state management, and human-in-the-loop experiences.
• Lead through hands-on engineering by writing, reviewing, and maintaining production-quality C# and Python code, including critical components, reference implementations, prototypes, and reusable platform capabilities.
• Own end-to-end technical delivery by translating ambiguous customer support scenarios into clear technical requirements and driving solutions from architecture and experimentation through implementation, deployment, operation, and continuous improvement.
• Define technical architecture and engineering standards, including architecture patterns, API and data contracts, code quality expectations, evaluation practices, deployment strategies, and observability standards for AI services.
• Advance evaluation-driven AI development by designing and implementing evaluation frameworks using rubrics, golden datasets, simulation, judge models, and offline and online evaluation, including quality thresholds and graduation criteria for autonomous operation.
• Own production quality and reliability across correctness, availability, latency, scalability, cost, and safety, and lead technical incident response, root cause analysis, and systemic improvements.
• Design for responsible and secure AI, including privacy protections, prompt-injection defenses, tool authorization, data boundaries, action controls, auditability, and fail-safe behavior.
• Make consequential technical decisions by evaluating models, frameworks, platforms, and architectural approaches using evidence from experiments and production telemetry, balancing quality with reliability, maintainability, latency, cost, and operational complexity.
• Influence product and platform roadmaps through collaboration with product managers, researchers, platform engineers, and Azure service teams, and by translating customer support patterns and operational signals into engineering investments.
• Drive measurable customer and business impact by instrumenting systems and using data to improve automation accuracy, case volume reduction, resolution time, engineering efficiency, and customer satisfaction.
• Provide technical leadership by leading architecture reviews, resolving complex technical disagreements, and aligning engineers and partner organizations around shared designs, with clear communication to technical and non-technical stakeholders.
• Raise organizational engineering capability by mentoring engineers in system design, software engineering, applied AI, and evaluation-driven development, including guidance on when AI agents should act autonomously.

Required Qualifications

• Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with 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: required to pass upon hire/transfer and every two years thereafter.

Technologies

• C, C++, C#, Java, JavaScript, Python
• LLM orchestration, multi-agent workflows, RAG
• Rubrics, golden datasets, simulation, judge models
• Offline and online evaluation
• Prompt-injection defenses

Preferred Qualifications

• 15 years of professional software engineering and enterprise architecture experience designing, building, integrating, and operating complex production software systems at enterprise scale.
• Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience (or) Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience, with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
• Deep hands-on software development background combined with enterprise architecture expertise, with experience translating business and technical requirements into scalable, resilient, maintainable system architectures.
• Proficiency in C# and/or Python, with demonstrated ability to design and implement production-quality services and distributed systems.
• Experience with applied AI systems, including LLM-based applications, prompt engineering, RAG architectures, agent frameworks, or machine learning services.
• Experience with cloud platforms, preferably Azure, and cloud-native engineering practices including microservices, APIs, containers, CI/CD, infrastructure as code, and observability.
• Proven ability to influence technical direction and align multiple teams without direct management authority.
• Experience implementing agent security patterns such as prompt-injection defense, identity propagation, least-privilege tool access, data-boundary enforcement, approval gates, and auditable actions.
• Demonstrated ability to move between strategic architecture and detailed implementation, including debugging complex interactions across models, prompts, tools, data, and distributed services.
• Proven business acumen connecting technical investments to measurable customer outcomes such as case volume reduction, resolution time, automation quality, and customer satisfaction.
• Track record of mentoring senior engineers and raising engineering standards across teams without formal people management responsibilities.
• Background in customer support engineering, supportability, diagnostics, or customer experience platforms is a plus.

Additional Information

• Some roles may be eligible for benefits and other compensation. More information: https://careers.microsoft.com/us/en/us-corporate-pay.
• Applications will be accepted on an ongoing basis until the position is filled, with the role open for a minimum of 5 days.