AI Platform Engineer

TEK INC
Dallas, United States
10 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

JavaScript (Programming Language) Artificial Intelligence Airflow Amazon Web Services Microsoft Azure Cloud Computing Continuous Integration Cursor Linux DevOps Disaster Recovery Distributed Systems
+26 more
Github Identity and Access Management Python (Programming Language) Machine Learning OAuth Open Source Technology OpenID Performance Tuning Role-Based Access Control Azure Machine Learning JSON Web Token Security Assertion Markup Language (SAML) Software Engineering Google Cloud GitHub Copilot Large Language Models Grafana Software Troubleshooting Generative AI AI Platforms Kubernetes Infrastructure Automation Frameworks Hardware Infrastructure Virtual Agents Terraform Docker

Job description

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., * 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., * AWS, Azure, Google Cloud Platform
  • AI/ML Platform Engineering
  • LangGraph
  • Google ADK
  • Claude Code
  • Codex
  • Cursor
  • GitHub Copilot
  • Kubernetes
  • Docker
  • Terraform
  • Helm
  • GitHub Actions
  • Python
  • JavaScript
  • OAuth 2.0, OIDC, IAM, RBAC
  • RAG
  • LangSmith
  • Grafana

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 (Google Cloud Platform)

  • 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.

Preferred Qualifications

  • 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.

Benefits & conditions

  • Competitive salary
  • Medical, Dental & Vision Insurance
  • 401(k) with employer contribution
  • Paid Time Off & Company Holidays
  • Professional Development Opportunities
  • Performance Bonus Program

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