Senior Engineer, AI
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Job Description
Senior AI Engineer at Carrington defining and governing Azure AI workload architecture for their AI program while ensuring compliance and security leadership.
Responsibilities:
- Design and document the secure-by-default reference architecture for AI workloads on Microsoft Azure, including identity, network isolation, secrets management, data boundaries, monitoring, and audit.
- Architect and operate production AI workloads on Azure AI Foundry, including model deployment, evaluation, and monitoring.
- Establish and operate an end-to-end AI governance framework — intake, risk classification, audit trail, and executive reporting — aligned to NIST AI RMF and ISO/IEC 42001.
- Define the design and security standard for Model Context Protocol (MCP) servers — authentication, transport, tool surface, least-privilege exposure, and audit — and curate the approved tool library.
- Design enterprise landing-zone and Well-Architected patterns for AI — subscription and management-group structure, policy guardrails, networking, and cost/quota strategy for Azure OpenAI and Foundry.
- Implement identity and access architecture using Microsoft Entra ID, RBAC, managed identities, and conditional access, including on-behalf-of flows for agentic applications.
- Define retrieval and data architecture patterns — RAG, Azure AI Search, embeddings, chunking, and retrieval-quality evaluation.
- Apply AI governance tooling — Microsoft Purview, custom Azure Policy, and Defender for Cloud — to AI workloads for data classification and security posture management.
- Document every AI workload in production — ownership, model, data, controls, evaluation, and runbook — so the platform is survivable and can be safely handed off.
- Author architecture decision records (ADRs), architecture briefs, and board-ready risk language for executive, legal, and risk stakeholders.
- Partner with the engineering team to onboard them against the reference architecture and tool library, and review designs for security and compliance.
- Stay current with advancements in the Azure AI platform, agent frameworks, and AI governance standards, and apply this knowledge to improve our foundation.
- Provide technical leadership and mentorship across the AI program.
- Ensure compliance with data privacy, security, and AI governance requirements.
Requirements:
- Demonstrated experience architecting and shipping production AI workloads on Azure AI Foundry, including model deployment, evaluation, and monitoring.
- Deep Azure security architecture expertise — private endpoints, managed identities, Key Vault, network isolation, and data-exfiltration controls for AI services — defensible at a whiteboard.
- Experience building or operating an AI governance framework end-to-end, with concrete application of NIST AI RMF or ISO/IEC 42001.
- Hands-on Model Context Protocol (MCP) server architecture — tool surface design, authentication, transport, and least-privilege reasoning — not solely consumption of MCP tools.
- Enterprise landing-zone and Well-Architected experience for AI workloads at scale, including subscription/management-group design, policy guardrails, and cost/quota strategy.
- Identity and access mastery: Microsoft Entra ID, RBAC, managed identities, conditional access, and on-behalf-of flows for agentic applications.
- Retrieval and data architecture: production RAG, Azure AI Search, embeddings, and retrieval-quality measurement.
- Governance tooling applied specifically to AI: Microsoft Purview data classification, custom Azure Policy, and Defender for Cloud posture management.
- Strong written communication for executive audiences — ADRs, architecture briefs, and risk language — and the ability to operate across legal, risk, and executive stakeholders.
- Excellent problem-solving, analytical, and communication skills, including the ability to document complex technical work clearly.
- Self-motivated, critical thinker able to lead architecture and governance workstreams to delivery in a small, high-ownership team.
- Ability to interact with all levels of the organization as an adviser on AI capabilities, governance, and business processes, and to make sound decisions that have significant impact on business operations.
- Ability to analyze and interpret complex data, and to compose detailed reports, business requirements, technical documentation, and group presentations.
- Bachelor's in Computer Science, Engineering, or equivalent experience required.
- 10+ years of professional software engineering and architecture experience, with a strong track record of delivering and operating production systems at enterprise scale.
- 5+ years of experience with Microsoft Azure required.
- 2+ years architecting production AI / LLM workloads required; hands-on experience with Azure AI Foundry strongly preferred.
- Demonstrated experience designing AI governance frameworks (NIST AI RMF or ISO/IEC 42001) and secure Azure architecture strongly preferred.
- Microsoft certifications such as Azure AI Engineer Associate (AI-102), Azure Solutions Architect Expert (AZ-305), or Cybersecurity Architect Expert (SC-100) are highly desirable.
- Public artifacts — reference architectures, technical writing, or talks — are a plus.
Benefits:
- Comprehensive healthcare plans for you and your family. Plus, a discretionary 401(k) match of 50% of the first 4% of pay contributed.
- Access to several fitness, restaurant, retail (and more!) discounts through our employee portal.
- Customized training programs to help you advance your career.
- Employee referral bonuses so you’ll get paid to help Carrington and Vylla grow.
- Educational Reimbursement.
- Carrington Charitable Foundation contributes to the community through causes that reflect the interests of Carrington Associates. For more information about Carrington Charitable Foundation, and the organizations and programs, it supports through specific fundraising efforts, please visit: __carringtoncf.org.__
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