Senior AI Platform Engineer

• Define standards-based deployment patterns for responsible AI agents, reusable platform capabilities, and secure agent runtime architectures, including identity, access, and secrets management.
• Automate AI platform buildout, release standardization, environment provisioning, CI/CD, Terraform/Helm deployments, and operational runbooks.
• Operate reliable AI platform services with incident response, capacity planning, Open Telemetry traces/logs/metrics, monitoring, rollback, and disaster recovery practices.
• Collaborate across Info Sec, Cloud Ops, Dev Ops, and platform engineering teams to create responsible agentic factory standards for guardrails, governance, secure releases, observability, and production readiness.
• Coach engineers, lead design reviews, guide implementation toward approved architecture patterns, and drive practical tradeoffs across cost, speed, reliability, and security.

• 8 to 10 years of engineering experience, including 7+ years building and operating production systems on cloud platforms, plus hands-on AI/ML service deployment in production.
• 2-3 years using AI coding tools (Claude Code, Codex, Cursor) to automate platform buildout, deployment, testing, troubleshooting, and documentation.
• Strong experience with GCP/AWS or hybrid cloud/datacenter deployments;
  Docker, Kubernetes, Git Hub Actions with reusable workflows and self-hosted runners, Terraform, and Helm.
• Working knowledge of authentication and authorization (OAuth 2.0, OIDC, SAML, JWT, RBAC, IAM), including workload identity, service-to-service auth, and securing API and tool access.
• 4+ years scripting and automation experience, preferably Python and JavaScript, with strong troubleshooting across Linux, containers, Kubernetes, networking, and production incidents.
• Ability to architect secure, cost-efficient hosting for open-source LLMs, on-prem or in dedicated cloud, as an alternative to commercial model APIs.

Demonstrates expertise in defining deployment patterns for responsible AI agents and automating AI platform buildout, with a strong focus on secure architectures and incident response. Proven ability to collaborate across teams and coach engineers in implementing best practices for production readiness.

• AI/ML Service Deployment
• Cloud Platform Engineering
• Terraform and Helm
• Authentication and Authorization
• Scripting and Automation

• AI Coding Tools
• Production Systems Engineering
• Incident Response
• Capacity Planning
• Monitoring and Observability
• Scripting in Python
• Scripting in Java Script
• Troubleshooting
• Deployment Automation
• Secure Architecture Design

• Coaching
• Collaboration
• Leadership
• Guidance

• Responsible AI
• Production Readiness
• Governance
• Guardrails
• Disaster Recovery

• GCP
• AWS
• Docker
• Kubernetes
• Git Hub Actions
• Open Telemetry
• CI/CD
• Linux
• RBAC
• IAM