{"id":2471922,"url":"https://alion.io/job/microsoft-principal-applied-ai-engineer-2","title":"Principal Applied AI Engineer","company":{"id":18,"name":"Microsoft","domain":"microsoft.com","url":"https://alion.io/company/microsoft","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"B","score":75,"open_postings":116,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-15T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Redmond, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":151000,"max_usd":310000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":691},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Azure","optional":false},{"name":"C#","optional":false},{"name":"C++","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"JavaScript","optional":false},{"name":"LLM","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"CI/CD","optional":true},{"name":"Least Privilege","optional":true},{"name":"Machine Learning","optional":true},{"name":"Prompt Engineering","optional":true}],"status":"live","first_seen_at":"2026-09-10T21:16:32Z","employer_posted_date":"2026-10-13","last_verified_at":"2026-10-16T00:43:07Z","board_verified":true,"closed_at":null,"days_open":35,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":35},"description":"OverviewAre you a customer-obsessed software engineer and technical architect who is passionate about applying AI to complex, real-world problems? The Engineering Operations (EngOps) team's mission is to transform Microsoft Cloud customers into fans. Through our deep engineering engagements with customers and teams across Microsoft, we analyze and amplify customer needs and drive the vision to improve cloud quality, security, and reliability. Our culture of growth mindset and empowerment is central to who we are and how we work.\nOur ACES CODE engineering team is building domain-specific agents and services that are fundamentally transforming Azure customer support, moving from reactive, human-only workflows to AI-first systems that resolve customer issues at Azure scale. We are seeking a Principal Applied AI Engineer to serve as a hands-on technical architect and senior developer for production agentic AI services.\nYou will define and implement the architecture for next-generation AI agents, including LLM orchestration, multi-agent coordination, retrieval-augmented generation (RAG), tool integration, and evaluation systems. You will write production code, lead complex technical initiatives, establish engineering standards, and guide engineers across organizational boundaries through technical influence rather than people management.\nThis is a deeply technical individual contributor role with broad architectural scope and direct accountability for production outcomes. You will turn ambiguous customer and business problems into scalable systems, make critical design decisions, build foundational components, and help teams ship secure and reliable AI services that handle thousands of customer cases per month.\nEvery day, our customers stake their business and reputation on our cloud. You can help Azure EngOps provide our customers with the world-class cloud services they need to succeed.\nMicrosoft's mission is to empower every person and every organization on the planet to achieve more. As employees, we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day, we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.\nResponsibilities\n'\nArchitect and build production agentic AI systems: Design and implement scalable AI agents and services, including LLM orchestration, multi-agent workflows, RAG pipelines, tool integrations, memory and state management, and human-in-the-loop experiences.\nLead through hands-on engineering: Write, review, and maintain production-quality C# and Python code. Build critical components, reference implementations, prototypes, and reusable platform capabilities that accelerate delivery across the engineering organization.\nOwn end-to-end technical delivery: Translate ambiguous customer support scenarios into clear technical requirements and take solutions from architecture and experimentation through implementation, deployment, operation, and continuous improvement.\nDefine technical architecture and engineering standards: Establish architecture patterns, API and data contracts, code quality expectations, evaluation practices, deployment strategies, and observability standards for AI services. Drive technical consistency while allowing teams to evolve their solutions.\nAdvance evaluation-driven AI development: Design and implement evaluation frameworks using rubrics, golden datasets, simulation, judge models, and offline and online evaluation. Define quality thresholds and graduation criteria for moving agents from experimentation through shadow mode and into autonomous operation.\nOwn production quality and reliability: Ensure AI services meet demanding standards for correctness, availability, latency, scalability, cost, and safety. Diagnose complex production issues, lead technical incident response and root cause analysis, and engineer systemic improvements.\nDesign for responsible and secure AI: Embed responsible AI principles, privacy protections, prompt-injection defenses, tool authorization, data boundaries, action controls, auditability, and fail-safe behavior into system architecture and implementation.\nMake consequential technical decisions: Evaluate models, frameworks, platforms, and architectural approaches using evidence from experiments and production telemetry. Balance solution quality with reliability, maintainability, latency, cost, and operational complexity.\nInfluence product and platform roadmaps: Partner with product managers, researchers, platform engineers, and Azure service teams to shape technical strategy and platform capabilities. Translate customer support patterns and operational signals into durable engineering investments.\nDrive measurable customer and business impact: Instrument systems and use data to improve automation accuracy, case volume reduction, resolution time, engineering efficiency, and customer satisfaction. Connect architectural investments to measurable outcomes.\nProvide technical leadership across teams: Lead architecture reviews, resolve complex technical disagreements, and align engineers and partner organizations around shared designs. Communicate clearly with engineering teams, senior leaders, and non-technical stakeholders.\nRaise the engineering capability of the organization: Mentor engineers in system design, software engineering, applied AI, and evaluation-driven development. Create reusable guidance and help teams develop the judgment to determine where AI agents should and should not act autonomously.\nQualifications\nBasic Qualifications\nBachelor'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.\nPreferred Qualifications\n8+ years of professional software engineering experience designing, building, and operating production software systems.\nStrong proficiency in C# and/or Python, with demonstrated ability to design and implement production-quality services and distributed systems.\nExperience with applied AI systems, including LLM-based applications, prompt engineering, RAG architectures, agent frameworks, or machine learning services.\nExperience with cloud platforms, preferably Azure, and cloud-native engineering practices including microservices, APIs, containers, CI/CD, infrastructure as code, and observability.\nProven ability to influence technical direction and align multiple teams without direct management authority.\nMaster's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.\nExperience implementing agent security patterns such as prompt-injection defense, identity propagation, least-privilege tool access, data-boundary enforcement, approval gates, and auditable actions.\nDemonstrated ability to move between strategic architecture and detailed implementation, including debugging complex interactions across models, prompts, tools, data, and distributed services.\nStrong business acumen and experience connecting technical investments to measurable customer outcomes such as case volume reduction, resolution time, automation quality, and customer satisfaction.\nTrack record of mentoring senior engineers and raising engineering standards across teams without formal people management responsibilities.\nBackground in customer support engineering, supportability, diagnostics, or customer experience platforms is a strong plus.\n#EngOps #EngOpsACES\nThis position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.\nMicrosoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. 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