Applied AI & Platform Engineer

<h2><strong>The Role</strong></h2> <p>As an Engineer in our newly established and rapidly growing AI team, you will build and operationalize high-value AI workflows across business use-cases, product integrations, and internal data intelligence (Data Lake). You will help extend our AI platform and shared services by delivering production-grade capabilities on our Azure infrastructure, integrating LLM functionality into reliable, secure, and observable systems, including scoped agent workflows that can be shipped, monitored, and iterated quickly.</p> <p>Success in this position requires strong engineering fundamentals, an operational mindset, and the ability to work autonomously while partnering effectively with technical and non-technical stakeholders across global teams.</p> <h2><strong>Key Responsibilities</strong></h2> <ul> <li>Build end-to-end workflow implementations from requirements to production: APIs, services, orchestration, and integrations</li> <li>Integrate AI capabilities into products and internal tools (LLM calls, tool/function calling, guardrails, evals, response structuring)</li> <li>Design and implement scoped agent workflows with clear boundaries, tools, permissions, fallbacks, and measurable outcomes</li> <li>Collaborate with vendors to deliver ROI-focused use-cases: define interfaces, validate delivery quality, and productionize outputs</li> <li>Establish strong observability: structured logging, tracing, metrics, dashboards, alerting, and runbooks</li> <li>Partner with data teams on Data Lake access patterns, workflows, metadata, governance, and reliability</li> </ul> <h2><strong>Essential Skills & Experience</strong></h2> <ul> <li>5-10 years professional software engineering experience; strong Python (services, APIs, testing)</li> <li>Cloud infrastructure experience (Azure preferred), operating production systems; cloud security fluency (identity, RBAC, secrets management, logging/auditing)</li> <li>CI/CD experience (Git-based pipelines, automated tests, deployment gates, rollback awareness)</li> <li>Strong testing, documentation, and operational discipline</li> </ul> <h2><strong> </strong><strong>Preferred skills & Experience  </strong></h2> <ul> <li>Data engineering fundamentals (schemas, pipelines, quality checks) within governed environments</li> <li>Infrastructure as Code (Bicep/Terraform), containerization (Docker), and API management patterns</li> <li>Agentic patterns (tool use, orchestration, state management) and practical guardrails</li> <li>Microsoft Graph and/or strong enterprise identity/API permissioning patterns</li> </ul> <h2><strong&g