You'll own complex AI initiatives end to end: partnering with applied science and engineering to shape architecture and integrated customer solutions — model selection, retrieval-augmented and agentic pipelines, prompt and tooling design, and safety guardrails. You'll drive the roadmap, schedules, and staging and release plans against clear objectives; lead governance across the AI development lifecycle (Responsible AI review, model-risk, privacy, and compliance); and validate outcomes against real telemetry. You'll own the customer supportability experience and act as a trusted technical person who evangelizes and drives the right work. An agent platform - an extensible, Model Context Protocol (MCP)-based system of AI diagnostic skills integrated with enterprise data services, run inside engineers' existing tools (CLI, VS Code, and chat). Production engineering rails - CI-enforced quality gates, evaluation regression testing, comprehensive data science telemetry, and supply-chain security that let us ship AI safely and at scale. Every system is instrumented to surface performance, adoption, and quality signals in real time. Language-model pipelines - training, fine-tuning (including RLHF), and automated evaluation of models that reason over and assess support cases. Quality-evaluation systems - rubric-based, LLM-as-judge evaluation that scores case handling and surfaces coaching and compliance signals. Intelligent case-routing services - classification and ranking models that route cases to the right team and catch misrouted cases early. Privacy-preserving data tooling - a redaction pipeline (pattern-matching → transformer models → LLM) that protects PII and secrets across every data flow, forming the trusted substrate the rest of the platform depends on. Bachelor's Degree in Computer Science, Information Technology (IT), or related field AND 5+ years technical support, technical consulting experience, or information technology experience OR equivalent experience. These requirements include, but are not limited to the following specialized security screenings: Bachelor's Degree in Computer Science, Information Technology, or related field AND 12+ years of technical support, technical consulting experience, or information technology experience OR equivalent experience. Industry IT-Based Certifications (e.g. Comp-TIA, CCNA, ISC2) 3+ years of experience developing and shipping production software services using TypeScript/Node.js, Python, or C#/.NET. Experience building AI-powered applications using large language models (LLMs), AI agents, MCP tools, prompt engineering, or machine learning techniques. Experience designing solutions that leverage Azure cloud services, large-scale datasets, Azure Data Explorer (Kusto), and retrieval technologies such as keyword, vector, or semantic search. Experience evaluating AI systems through model evaluation frameworks, labeled datasets, RLHF, preference-based training, or LLM-as-a-judge methodologies. Experience implementing software quality and security practices, including automated testing, code reviews, CI/CD pipelines, code scanning, dependency management, and branch governance. Experience developing privacy, compliance, or data protection solutions, including PII detection and data redaction. Experience building customer-facing, support, or enterprise operations applications.
Want jobs like this matched to you?
SimpleCareer scores fresh postings against your résumé so you only see the matches that matter.