AI Engineer
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Role details
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Job description
This role will shape architecture, standards, framework and execution for an agentic AI platform, AI model governance, AI cost management, and enterprise platform integrations. You will partner with security, infrastructure, and business leaders to establish a scalable AI operating model that accelerates value while maintaining strong controls, policy compliance, and financial stewardship., * Lead engineer for agentic AI derivation and deployment platform. Work would include curation agent workflows, agent specification generation, and automated provisioning in Azure Foundry.
- Define and implement enterprise patterns for AI agent lifecycle management, security controls, policy enforcement, and operational observability.
- Lead model evaluation and recommendation activities in partnership with security and governance teams, including trade off analysis across capability, risk, and cost.
- Key contributor to discussions on AI credit management capabilities, including forecasting, allocation strategies, usage analytics, and executive level reporting.
- Build and govern automation frameworks for usage reporting, model controls, policy checks, and operational remediation.
- Serve as technical resource on AI cloud platforms for the enterprise: GitHub, Foundry, Codex, etc
- Guide integration strategy for AI experiences across APIs, workflows, M365 Copilot, SharePoint Online, Teams, and related enterprise tools.
- Mentor junior engineers, define engineering standards, and drive delivery excellence across AI/automation initiatives.
- Partner with platform teams on Azure Foundry infrastructure posture, security hardening, and compliance adherence.
- Evaluate emerging AI tools and establish adoption guidance, architecture guardrails, and implementation roadmaps.
Requirements
- Due to contract requirements, U.S. citizenship and successful completion of a CGI background check are required prior to the start of work.
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field; advanced degree preferred but not required.
- 5+ years of experience in software engineering, cloud engineering, or automation platforms, with at least 2+ year in AI/ML enabled solution delivery.
- Experienced full stack developer with focus on AI.
- Proven experience designing and deploying production grade cloud solutions on Azure.
- Strong proficiency in Python, PowerShell, and SQL; ability to build robust API driven automation systems.
- Working knowledge in Azure ML, Azure Functions, Cognitive Services, Azure Foundry Agent Services, Azure Automation Accounts (Runbooks).
- Demonstrated expertise with RESTful APIs, service integration, and secure authentication/authorization patterns.
- Experience establishing technical governance, architecture standards, and secure by design practices in enterprise environments.
- Experience with cost optimization, usage analytics, budgeting, or FinOps style engineering for cloud/AI services.
- Excellent stakeholder communication skills and ability to translate complex technical topics for security, finance, and business audiences.
- Demonstrated leadership in mentoring engineers, driving architecture decisions, and delivering cross functional programs.
Desired qualifications/non essential skills required:
- Working knowledge in Azure ML, Azure Functions, Cognitive Services, Azure Foundry Agent Services, Azure Automation Accounts (Runbooks).
- Hands on experience with Azure Foundry and enterprise agent/LLM orchestration patterns.
- Experience implementing policy as code, compliance checks, and governance automation for AI platforms.
- Familiarity with GitHub Enterprise Cloud administration, billing governance, and AI policy management.
- Experience integrating with M365 services (SharePoint Online, Teams, Graph APIs) and Copilot adjacent tooling.
- Experience with Dataverse via REST APIs and enterprise data platform integrations.
- Exposure to Copilot Studio administration or enterprise advisory support.
- Experience building reusable AI platform components, internal developer platforms, or “factory” style delivery models.
- Relevant certifications (Azure Solutions Architect, Azure AI Engineer, Security, or DevOps) are a plus.
Skills:
- Artificial Intelligence
- Azure
- English
- Azure API Management
- Python
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