DEVOPS / MLOPS ENGINEER – NODA AI

Location: Austin, TX (Hybrid on-site, with up to 10% travel)
Clearance Requirement: U.S. Citizen with the ability to obtain a security clearance

REQUIRED QUALIFICATIONS

• 3+ years of DevOps or MLOps engineering experience.
• Proficiency with Kubernetes, Docker, and CI/CD pipelines (GitHub Actions, Jenkins).
• Experience with cloud infrastructure (AWS/Azure/GCP) and on-prem hybrid deployments.
• U.S. Citizenship with the ability to obtain a clearance.

PREFERRED QUALIFICATIONS

• Experience deploying AI/ML models in production (LangChain, transformers, PyTorch).
• Familiarity with agentic AI workflows and emerging AgentOps concepts (agent lifecycle, monitoring, safe deployment).
• Experience with edge compute deployment (Jetson, Pi).
• Exposure to defense/DoD environments and IL-compliant infrastructure.
• Familiarity with ROS2, Gazebo, or robotic middleware.

SKILLS & ATTRIBUTES

• Obsessed with automation, reliability, and repeatability.
• Ability to debug complex deployments across simulation and field environments.
• Collaborative mindset with autonomy, AI, and field engineering teams.
• Comfortable balancing rapid iteration with security and compliance constraints.

THE ROLE

You’ll own the CI/CD, infrastructure automation, and ML model deployment tooling that allows agentic AI orchestration and multi-vehicle autonomy. This includes building repeatable workflows for simulation, test, and live field events while enforcing DoD-grade security and compliance.

KEY RESPONSIBILITIES

• Build and maintain CI/CD pipelines for software deployment across simulation, integration, and field environments.
• Manage containerized microservices (Docker, Kubernetes) with ROS2 integration to support orchestration and autonomy stacks.
• Develop automation for simulation-based validation and swarm-level regression testing.
• Implement MLOps pipelines for updating and validating AI workflows, including prompt/constraint updates.
• Support deployment to edge compute nodes (Jetson, Pi) and tactical environments with constrained bandwidth.
• Implement observability tooling (logs, metrics, telemetry dashboards) to validate multi-domain orchestration.
• Enforce security and compliance standards (DoD IL5/6, Zero Trust, IAM, encryption).
• Contribute to early AgentOps workflows (e.g., prompt versioning, reasoning trace capture, agent replay/debug) in collaboration with AI engineers. Familiarity a plus but not required at entry.