AI Platform Architect

This is a fully remote position, open to applicants in United States.

📋 Description

• Administer and configure AI tools and platforms such as Claude, MS Copilot, GitHub Copilot, and LLM APIs.

• Provision tools, set up features, monitor usage, and optimize platforms in collaboration with IT administration, infrastructure, and ServiceDesk.

• Manage the registry, access control, and infrastructure that supports prompt libraries, skills, repeatable workflows, MCP servers, and connectors.

• Develop and implement lightweight internal tools and automation, including deployment scripts, self-service provisioning, usage and cost dashboards, and monitoring solutions.

• Create and sustain dashboards that track adoption, usage, cost-per-tool, and ROI for both internal and product-embedded AI initiatives.

• Oversee the health of AI tools, including token and compute costs, anomalies, and cloud operations related to AI workloads.

• Collaborate with Engineering and IT on LLM API operations and the deployment of cloud resources.

• Configure and assess security settings for MCP servers, connectors, and AI tools.

• Work alongside InfoSec on the security approval and monitoring of AI tools.

• Maintain libraries for AI FAQs and security questionnaires.

• Address enterprise AI security reviews and contribute AI-specific content to RFP responses, compliance questionnaires, and contracting support.

• Assist in AI vendor due diligence and third-party risk assessments.

• Create and uphold AI governance documentation, including risk frameworks, AI workflow catalogs, and protocols for handling PHI.

⛳️ Requirements

• Daily hands-on experience with modern AI and agentic tools.

• Proven experience in configuring, deploying, or administering AI tools for others.

• Initiative and resourcefulness in AI, demonstrated through self-directed learning, side projects, or internal experiments.

• 3–5 years of experience in technical roles that include cloud, platform, DevOps, or AI operations.

• Experience preferably within healthcare or another regulated industry.

• Practical cloud experience across GCP, Azure, or AWS.

• Experience in provisioning and configuring cloud resources.

• Familiarity with containers/services such as Docker, Kubernetes, or similar technologies.

• Proficiency in scripting and automation, particularly in Python or related languages.

• Strong skills in data analysis, reporting, and dashboard creation.

• Experience administering enterprise SaaS platforms, covering user management, SSO configuration, usage analytics, and cost tracking.

• Working knowledge of HIPAA Privacy/Security Rules, SOC 2 Type II, or HITRUST frameworks and their relevance to AI tooling.

• Excellent technical writing skills for documentation, governance, and security artifacts.

• Preferred: hands-on experience with DevOps tooling, specifically CI/CD and Infrastructure-as-Code, such as Terraform.

• Preferred: experience with cloud cost management and FinOps practices.

• Preferred: understanding of AI/ML-specific security considerations, including model governance, prompt-injection risks, MCP/connector security, and data handling.

• Preferred: familiarity with enterprise AI platforms such as Vertex AI, Azure AI Foundry, or Bedrock.

• Preferred: knowledge of BI/analytics pipelines including BigQuery, SQL, and Python.

• Preferred: a background in healthcare data exchange, including FHIR, HL7, and clinical data workflows.

🏝️ Benefits

• Annual cash bonus.

• Medical insurance.

• Dental insurance.

• Vision insurance.

• Life insurance.

• 401(k) plan.

• Comprehensive benefits offering.