Note: The job is a remote job and is open to candidates in USA. Charter Global is seeking an AI Platform Engineer who will translate AI reference architectures into secure, scalable cloud configurations for AI solutions in a regulated healthcare environment. This role involves operationalizing platform standards, automating guardrails, and ensuring compliance with enterprise security and governance 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
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
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