Direct hire AI Platform Engineer

Saxon Global • Richardson, TX

1d • Hybrid

About The Position

We are seeking a Senior AI Platform Engineer to build and scale enterprise AI platforms that support secure, reliable, and production-ready AI applications. This role is ideal for an experienced engineer with expertise in cloud infrastructure, Kubernetes, AI/ML deployment, CI/CD automation, and modern AI agent frameworks. You will play a key role in designing AI platform architecture, establishing engineering standards, and enabling responsible AI adoption across the organization.

Requirements

• 8–10 years of software engineering experience with at least 7 years building and operating production cloud platforms.
• Hands-on experience deploying AI/ML solutions into production environments.
• 2–3 years of experience using AI-assisted development tools such as Claude Code, Codex, Cursor, GitHub Copilot , or similar.
• Strong experience with one or more cloud platforms: AWS Azure Google Cloud Platform (GCP)
• Strong expertise in: Docker Kubernetes Terraform Helm GitHub Actions or equivalent CI/CD tools
• Experience securing enterprise platforms using OAuth 2.0, OIDC, SAML, JWT, RBAC, and IAM.
• Experience implementing workload identity and secure service-to-service authentication.
• 4+ years of scripting and automation using Python and JavaScript.
• Strong troubleshooting experience across Linux, containers, Kubernetes, networking, and distributed systems.
• Experience designing secure, cost-effective hosting solutions for open-source LLMs.

Nice To Haves

• Experience with AI agent frameworks such as LangGraph and Google ADK .
• Knowledge of: Retrieval-Augmented Generation (RAG) AI workflow orchestration Agent-to-agent communication Tool integrations AI evaluation frameworks Guardrail implementation
• Experience with observability platforms such as LangSmith and Grafana/LGTM .
• Familiarity with GPU infrastructure for AI model serving.
• Experience with workflow orchestration tools such as Dagster, Prefect, or Apache Airflow .
• Strong leadership, communication, mentoring, and stakeholder management skills.

Responsibilities

• Design and implement scalable, secure AI platform infrastructure for production AI workloads.
• Build standardized deployment patterns for AI agents and reusable platform services.
• Automate infrastructure provisioning, CI/CD pipelines, environment management, and Infrastructure as Code (Terraform, Helm, GitHub Actions).
• Manage AI platform operations, including monitoring, observability, incident response, capacity planning, disaster recovery, and performance optimization.
• Partner with Security, DevOps, Cloud, and Platform Engineering teams to establish governance, compliance, and production readiness standards.
• Implement secure authentication and authorization using OAuth 2.0, OIDC, SAML, JWT, RBAC, and IAM.
• Develop automation and tooling using Python and JavaScript.
• Mentor engineering teams, conduct design reviews, and promote engineering best practices for scalability, security, reliability, and cost optimization.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed