Note: The job is a remote job and is open to candidates in USA. Dice is seeking a Senior AI Platform Engineer to translate AI reference architectures into secure, scalable cloud configurations for a regulated healthcare environment. The role involves operationalizing platform standards, automating guardrails, and ensuring that AI workloads meet security and compliance requirements.
Responsibilities
- Convert approved AI reference architectures into deployable cloud configurations across Azure, MuleSoft, and Salesforce Agentforce, using infrastructure-as-code (Terraform, Bicep, ARM) and CI/CD pipelines
- Build and maintain reusable platform components, modules, and landing zones that accelerate AI solution delivery across product teams
- Configure and operate core AI platform services (e.g., Azure OpenAI, Azure AI Foundry, AI Search, MuleSoft integration layers, Salesforce Agentforce agents, Antrhopic, OpenAI) in alignment with enterprise architecture standards
- Implement environment promotion patterns (dev --€-'''''''' test --€-'''''''' prod), secrets management, and observability tooling for AI workloads
- Translate AI governance policies (risk tiering, model approval, PHI/PII handling, audit logging) into enforceable technical controls: policy-as-code, Azure Policy, RBAC, network isolation, and data egress restrictions
- Implement controls that enforce HIPAA, CMS, and internal compliance requirements for AI solutions, including Zero Data Retention configurations, audit log integration, and prompt/response logging where required
- Partner with the AI Governance Lead and Coordinator to ensure platform configurations match documented governance posture and are audit-ready
- Configure model gateways, content safety filters, bias/PII safeguards, and usage telemetry to support responsible AI operations at scale
- Deliver paved-path templates, starter kits, and self-service capabilities that allow product and engineering teams to build AI solutions safely without recreating platform components
- Provide technical support, documentation, and office hours to development teams consuming the AI platform
- Collaborate with Consultant Product Owners and platform architects to translate solution requirements into platform capabilities and backlog items
- Monitor platform health, capacity, cost, and consumption; implement automation to optimize spend and performance
- Support incident response, root-cause analysis, and continuous improvement of platform reliability and security posture
- Maintain platform documentation, runbooks, and architectural decision records
Skills
- Bachelor's degree in Computer Science, Engineering, or related field; equivalent experience considered
- 5+ years of cloud platform engineering experience, with 2+ years focused on Azure (or comparable hyperscaler)
- Hands-on experience with infrastructure-as-code (Terraform/Bicep), CI/CD pipelines (Azure DevOps, GitHub Actions), and policy-as-code frameworks
- Working knowledge of AI/ML platform services Azure OpenAI, AI Foundry, vector databases, model gateways, or equivalent
- Experience implementing technical controls for regulated data environments (HIPAA, PCI, or similar)
- Strong understanding of identity, networking, encryption, and secrets management patterns in the cloud
- Platform familiarity across Azure, MuleSoft, and Salesforce Agentforce ability to configure, integrate, and govern AI workloads spanning all three platforms
- Experience operating AI or data platforms in a healthcare payer or other regulated industry
- Familiarity with AI governance frameworks (NIST AI RMF, ISO 42001) and translating policy into technical enforcement
- Experience with document intelligence, RAG architectures, or agentic AI patterns
- Azure certifications (AZ-305, AZ-400, AI-102), MuleSoft Certified Developer/Architect, or Salesforce Agentforce/Platform credentials a plus
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