Sr AI Platform Engineer

BravoTECH; Richardson (TX); On-site; USD 170,000 - 250,000; Full time

Job summary

BravoTECH seeks a Senior Lead AI Platform Engineer in Richardson, TX to build an enterprise AI platform from the ground up, enabling internal teams to securely deploy and operate AI workloads at scale. The role focuses on platform engineering, cloud infrastructure, Kubernetes, DevOps and automation.

You will design production-ready infrastructure, set engineering standards, and drive reliable AI deployments across cloud environments.

Qualifications

• 8–10 years of software or platform engineering experience.
• 7+ years building and operating production systems in AWS, GCP, or hybrid clouds.
• 2+ years deploying AI/ML services in production.
• 4+ years scripting in Python and/or JavaScript.
• Strong experience with Docker, Kubernetes, GitHub Actions, Terraform, and Helm.
• Designing secure auth: OAuth 2.0, OIDC, SAML, JWT, RBAC, IAM.
• Strong Linux, Kubernetes, networking, and production troubleshooting.

Responsibilities

• Design and implement secure, scalable AI platform architectures.
• Automate infrastructure provisioning, CI/CD pipelines, and deployments.
• Operate highly available AI platform services with observability and DR.
• Collaborate with cloud, DevOps, platform, and security teams on governance.
• Lead design reviews, mentor engineers, and promote secure solutions.
• Improve reliability and efficiency through automation and standardization.

Skills

Platform engineering

Cloud infrastructure

Mentoring engineers

Tools

Docker

Kubernetes

GitHub Actions

Terraform

Helm

OAuth 2.0

OIDC

Job description

Senior Lead AI Platform Engineer

Build the Future of Enterprise AI Platforms

In this role you'll build an enterprise AI Platform from the ground up that will enable internal engineering teams to securely deploy and operate agentic AI workloads at scale. The focus is on platform engineering, cloud infrastructure, Kubernetes, DevOps, and end-to‑end automation rather than developing AI models. In this role, you'll design and automate production-ready AI infrastructure, establish engineering standards, and help drive reliable, governed AI deployments across cloud environments. You'll work closely with platform, security, and cloud engineering teams while mentoring engineers and shaping best practices for modern AI operations.

Key Responsibilities

• Design and implement secure, scalable AI platform architectures and reusable deployment patterns.
• Automate infrastructure provisioning, CI/CD pipelines, and platform deployments using Infrastructure as Code.
• Build and operate highly available AI platform services with monitoring, observability, disaster recovery, and incident response practices.
• Partner with cloud, DevOps, platform, and security teams to establish AI governance, deployment standards, and operational best practices.
• Lead technical design reviews, mentor engineers, and promote scalable, secure engineering solutions.
• Improve platform reliability, deployment consistency, and operational efficiency through automation and standardization.

Required Qualifications

• 8–10 years of software or platform engineering experience, including 7+ years building and operating production systems in AWS, GCP, or hybrid cloud environments.
• Hands‑on experience deploying and supporting AI/ML services in production.
• 2+ years using AI‑assisted development tools such as Claude Code, Codex, or Cursor.
• Strong experience with Docker, Kubernetes, GitHub Actions, Terraform, and Helm.
• Experience designing secure authentication and authorization solutions using OAuth 2.0, OIDC, SAML, JWT, RBAC, and IAM.
• 4+ years of scripting and automation experience using Python and/or JavaScript.
• Strong troubleshooting skills across Linux, Kubernetes, networking, containers, and production environments.
• Experience designing secure, cost‑effective infrastructure for hosting large language models (LLMs).

Preferred Qualifications

• Experience with agentic AI frameworks such as LangGraph or Google ADK.
• Knowledge of AI orchestration, RAG architectures, tool calling, evaluation frameworks, and responsible AI practices.
• Experience with AI observability tools such as LangSmith, Grafana, or LGTM.
• Familiarity with GPU infrastructure, Vertex AI, NVIDIA GPU Operator, or model serving platforms.
• Experience with workflow orchestration tools such as Dagster, Prefect, or Airflow.
• Strong communication, mentoring, stakeholder management, and technical leadership skills.

Why Join Us

Build enterprise-scale AI platforms using modern cloud and automation technologies. Influence engineering standards and best practices for AI infrastructure. Work with cutting‑edge AI technologies in a collaborative, innovation‑focused environment. Mentor talented engineers while helping shape the future of responsible AI delivery.