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Senior Applied AI Engineer

Microsoft· Software Engineering
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Redmond, WA, Atlanta, GA$119.8k - $234.7kfull-timePosted 4d ago

About the role

Senior applied AI engineer within Azure EngOps ACES CODE team designing, building, and operating production agentic AI services using LLM orchestration, retrieval-augmented generation, and agent workflows to improve Azure customer support and product quality.

Responsibilities

  • Design and build production AI services: Develop scalable agentic AI solutions using LLM orchestration, RAG pipelines, agent workflows, tool integrations, memory and state management, and human-in-the-loop experiences.
  • Lead through hands-on engineering: Write, review, test, and maintain production-quality C# and Python code. Build reusable components, reference implementations, and engineering patterns that accelerate team delivery.
  • Own end-to-end technical delivery: Translate customer support scenarios and product requirements into technical designs, then take solutions through implementation, testing, deployment, monitoring, and continuous improvement.
  • Build evaluation-driven AI systems: Develop evaluation frameworks using rubrics, golden datasets, simulations, judge models, and offline and online evaluation. Use measurable quality thresholds to guide agents from experimentation toward production operation.
  • Engineer for production quality: Ensure services meet requirements for correctness, reliability, availability, latency, scalability, maintainability, cost, and safety.
  • Implement secure and responsible AI patterns: Apply privacy protections, prompt-injection defenses, least-privilege tool access, identity and authorization controls, data boundaries, approval gates, auditability, and fail-safe behavior.
  • Integrate with Azure services and data sources: Ground agent responses and actions in trusted, current signals by integrating with Azure data sources, APIs, and cloud-native services.
  • Operate services in production: Implement CI/CD, automated testing, feature flags, staged rollouts, tracing, logging, metrics, and alerting. Diagnose production issues, participate in incident response, and drive corrective improvements.
  • Make evidence-based technical decisions: Evaluate models, frameworks, prompts, retrieval approaches, and architectural options using experiments and production telemetry. Balance quality with reliability, latency, cost, maintainability, and operational complexity.
  • Drive measurable customer impact: Instrument solutions and use data to improve automation quality, case-volume reduction, resolution time, engineering efficiency, and customer satisfaction.
  • Provide technical leadership within projects: Lead design reviews, resolve technical challenges, coordinate implementation across contributors, and align partner teams around shared interfaces and delivery goals.
  • Mentor and raise engineering capability: Support other engineers through code reviews, technical guidance, reusable documentation, and practical coaching in applied AI and production software engineering.
  • Collaborate across organizational boundaries: Partner with product managers, researchers, platform engineers, Azure service teams, and support-domain experts to deliver durable solutions and shape future platform capabilities.

Qualifications

  • Bachelor's Degree in Computer Science or related technical field AND 4+ 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 security screening requirements (Microsoft Cloud Background Check) as part of hire/transfer and every two years thereafter.

Skills

Required:LLM orchestrationretrieval-augmented generation (RAG)production software engineeringAzure services integration
Nice to have:agent frameworkssecurity patterns for AIevaluation frameworksdistributed systems
Last updated Oct 23, 2026. Interested? Apply on the company site.

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