The Principal Applied AI Engineer role at ACES CØDE involves serving as a hands-on technical architect and senior developer for production agentic AI services. The team focuses on transforming Azure customer support from reactive workflows to AI-first systems capable of autonomous issue resolution. This deeply technical individual contributor position requires defining and implementing architecture for next-generation AI agents while ensuring production quality and reliability. The role emphasizes collaboration across teams and driving measurable customer impact through innovative engineering solutions.

• Bachelor's Degree in Computer Science or related technical field AND 6+ years of technical engineering experience with coding in languages including C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
• Ability to meet Microsoft, customer and/or government security screening requirements.
• 15 years of professional software engineering and enterprise architecture experience designing, building, integrating, and operating complex production software systems at enterprise scale is preferred.
• Master's Degree in Computer Science or related technical field AND 8+ years of technical engineering experience OR Bachelor's Degree in Computer Science or related technical field AND 12+ years of technical engineering experience is preferred.
• Proficiency in C# and/or Python with demonstrated ability to design and implement production-quality services and distributed systems is preferred.
• Experience with applied AI systems, including LLM-based applications and machine learning services is preferred.
• Experience with cloud platforms, preferably Azure, and cloud-native engineering practices is preferred.

• Architect and build production agentic AI systems including LLM orchestration and multi-agent workflows.
• Write, review, and maintain production-quality C# and Python code.
• Translate ambiguous customer support scenarios into clear technical requirements.
• Establish architecture patterns, API and data contracts, and code quality expectations for AI services.
• Design and implement evaluation frameworks for AI development.
• Ensure AI services meet standards for correctness, availability, and scalability.
• Embed responsible AI principles and privacy protections into system architecture.
• Evaluate models and architectural approaches using evidence from experiments.
• Partner with product managers and engineers to shape technical strategy.
• Instrument systems to improve automation accuracy and customer satisfaction.
• Lead architecture reviews and resolve complex technical disagreements.
• Mentor engineers in system design and applied AI.

• Employees at Microsoft are often offered comprehensive, “world-class” benefits—including health and mental-wellness programs, competitive pay with bonuses and stock awards, and retirement/savings options. Time-off and flexibility are common, with generous vacation and holidays, parental and caregiver leave, and flexible work schedules, alongside learning support, employee resource groups, product discounts, and matching-gifts/volunteering programs. Specific benefits can vary by region.