Remote Foundry Pattern Maker Jobs in Dallas, TX (NOW HIRING)

Job Overview:

Requirement/Must Have:

• 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.

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.

Nice to Have:

• 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.