Engineer, AI, Senior
Bakersfield, Kern County, California, 93301, USA
Listed on 2026-06-27
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IT/Tech
AI Engineer (Applied/Software)
Come join our amazing team and work from home !
Responsible for defining, documenting, and governing the secure‑by‑default foundation on which the company's AI program operates. This is a hands‑on architecture role: designing the reference architecture for AI workloads on Microsoft Azure, establishing the AI governance and oversight model, documenting the systems already in production, and curating the reusable library of approved tools and Model Context Protocol (MCP) servers that the rest of the organization builds on.
Perform all duties in accordance with the company's policies and procedures, and all US state and federal laws and regulations, wherein the company operates. The target pay range for this position is $117,000 to $150,000 .
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 , 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.
What you’ll needDemonstrated 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 , 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 —…
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