Senior Applied AI Engineer

Build agentic resolution capabilities for AFO Build and improve agentic patterns that raise autonomous resolution rate, accuracy, and customer satisfaction, contributing to the team's technical execution. Deliver engineering for Agentic AI solutions Deliver end-to-end features across autonomous AI systems, including orchestration, reasoning, retrieval, action execution, and human escalation workflows. Take capabilities from prototype through production across support surfaces while partnering effectively across dependent engineering teams. Contribute to technical direction and engineering standards Help shape the technical foundation for agent development by implementing architectures, design patterns, evaluation frameworks, and reusable platform capabilities. Apply and help improve standards for prompts, tool interfaces, testing, versioning, code quality, CI/CD, and safe deployment practices (shadow, canary, progressive rollout, automated rollback) so agent behavior remains reliable, observable, and scalable. Build evals that improve customer confidence that our agents are trustworthy in understanding customer sentiment and intent and in validating agentic actions. Contribute to production health and reliability Help run the service with a DevOps/SRE operating model. Support availability, latency, cost per resolution, SLOs and error budgets, regression detection, incident response, and the on-call rotation for a fleet of agents acting autonomously in the customer path. Build the observability needed to explain why an agent did what it did, and drive durable fixes rather than repeated mitigations. Build and maintain evaluation systems Contribute to the evaluation framework that determines whether agents are safe and effective in production. Build and maintain golden datasets, rubrics, judge agents, frozen anchors, and offline/online evaluation pipelines. Use evaluation signals to gate releases and continuously improve quality through production feedback loops. Contribute to measurable business impact Help move key business outcomes, including support demand reduction, autonomous resolution rate, resolution quality, time-to-resolution, engineer productivity, and customer satisfaction. Ensure the capabilities you build are measurable and directed toward the highest-impact opportunities. Turn Customer Signals into Engineering Insight Build mechanisms that convert unresolved cases, customer feedback, and dissatisfaction signals into actionable engineering insights. Help ensure recurring failure patterns improve future agent capabilities and route product fixes back to the appropriate engineering teams. Grow your craft and share learnings Deepen your agentic AI and DevOps craft, and extend the team's impact by sharing proven patterns, tools, and operational learnings with your peers. Bachelor's Degree in Computer Science, Engineering, or related field AND +8 years technical engineering experience in software engineering, applied AI/ML, or distributed systems, OR equivalent experience. 8+ years of IT experience and 3+ years of experience using Agentic AI Demonstrated hands-on experience building and shipping AI or machine learning systems in production. Demonstrated DevOps or SRE background: hands-on experience with CI/CD and release engineering, safe-deployment practices (e.g., blue/green, canary, progressive rollout, automated rollback), observability and monitoring, and participation in production incident response and on-call for always-on services. Master's degree in Computer Science, AI, or a related field. Experience building and shipping multi-agent orchestration systems or agentic AI services in production. Experience with AI evaluation frameworks: rubrics, golden datasets, judge agents, offline and online evaluation. Experience with Azure AI Foundry, Azure OpenAI, or comparable enterprise AI platforms. Familiarity with agent security patterns: prompt injection defense, tool access controls, data boundary enforcement. DevOps/SRE toolchain depth: CI/CD pipelines, infrastructure-as-code, deployment automation, and progressive-delivery tooling (shadow, canary, feature/rollout gating, automated rollback). Observability engineering: building tracing, metrics, and logging for distributed or agentic systems and using them to drive durable fixes rather than repeated mitigations. Reliability practice: working with SLIs/SLOs and error budgets and taking part in the operational rhythm (live-site reviews, post-incident reviews, repair-item and corrective-action tracking) that keeps a fleet healthy. Experience contributing to cross-org or co-development engineering delivery with partner teams. Business acumen, with the ability to connect engineering work to measurable customer and business outcomes. Background in customer support engineering, supportability, or customer experience platforms. Experience operating always-on production services, including on-call participation and incident response. This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. *