Platform Engineer II/III

About the role

We're seeking a Platform Engineer to architect and operate scalable compute infrastructure that powers our autonomous vehicle simulation and testing framework. You will build elastic compute systems across AWS and on-premises clusters, enabling engineering teams to rapidly iterate on autonomy algorithms through massive parallel simulation workloads.

Responsibilities

• Elastic Compute Architecture
  • Design and implement auto-scaling compute infrastructure for simulation workloads using cloud platforms
  • Build and maintain on-premises GPU and CPU clusters for simulation and machine learning training
  • Architect hybrid cloud solutions that optimize cost and performance across cloud and local compute resources
  • Implement job scheduling and orchestration systems using Kubernetes for thousands of concurrent simulations
  • Design storage solutions for large-scale simulation data, logs, and artifacts using cloud and local storage systems
• Simulation Platform Development
  • Deploy and maintain robotics simulation environments at scale
  • Build CI/CD pipelines for automated simulation testing of autonomy software
  • Create infrastructure for distributed parameter sweeps, Monte Carlo testing, and regression suites
  • Develop monitoring and observability systems for simulation fleet health and resource utilization
  • Implement data pipelines for simulation results ingestion, analysis, and visualization
• Infrastructure as Code & Automation
  • Write and maintain infrastructure as code for reproducible infrastructure deployment
  • Build automation tools and CLI utilities to simplify developer access to compute resources
  • Implement GitOps workflows for infrastructure changes and configuration management
  • Create self-service interfaces for engineers to launch and manage simulation jobs
  • Develop cost monitoring and optimization strategies for cloud and on-prem resources
• System Operations & Reliability
  • Monitor and optimize infrastructure performance, reliability, and cost efficiency
  • Troubleshoot complex distributed systems issues across networking, storage, and compute layers
  • Implement backup, disaster recovery, and business continuity strategies
  • Maintain security best practices including IAM, secrets management, and network isolation
  • Collaborate with autonomy, ML, and robotics teams to understand compute requirements and optimize workflows
• Network Design & Infrastructure
  • Design and implement network architectures for distributed simulation workloads across AWS and on-premises environments
  • Configure VPCs, subnets, security groups, and routing for secure, high-performance compute clusters
  • Establish hybrid cloud connectivity (VPN, Direct Connect, site-to-site tunnels) between on-premises and cloud resources
  • Optimize network performance for large data transfers, multi-node communication, and distributed workloads
  • Support internal infrastructure network design and provide technical guidance to engineering programs
  • Troubleshoot network issues including latency, packet loss, and connectivity problems across distributed systems

Requirements

• Bachelor's in Computer Science, Software Engineering, or related technical field – equivalent industry experience also welcome
• 2-5+ years of experience in platform engineering, DevOps, SRE, or cloud infrastructure roles
• Strong hands-on experience with Kubernetes for container orchestration and workload management
• Experience with cloud computing platforms and services (compute, storage, networking)
• Deep understanding of Linux system administration and troubleshooting
• Strong networking fundamentals including TCP/IP, routing, DNS, VPNs, and security
• Understanding of infrastructure as code principles and configuration management
• Proficiency in scripting and automation (Python, Bash, or similar)
• Experience building and maintaining CI/CD pipelines
• Solid grasp of distributed systems concepts, job scheduling, and resource management
• Ability to design infrastructure from first principles and make architectural decisions

Preferred Qualifications

• Experience building infrastructure for simulation, robotics, or autonomous systems workloads
• Understanding of GPU computing and accelerated workload management
• Knowledge of job scheduling systems for batch and parallel workloads
• Experience managing on-premises clusters and hybrid cloud architectures
• Familiarity with robotics middleware (ROS/ROS2) or simulation platforms
• Understanding of cost optimization for compute-intensive workloads
• Experience with monitoring, logging, and observability systems
• Knowledge of containerization technologies and image management
• Background in data engineering, MLOps, or machine learning infrastructure
• Experience with network performance analysis and troubleshooting
• Understanding of software-defined networking and network automation
• Familiarity with security compliance requirements in aerospace/defense environments

Pay

Level II - $113,000 - $141,000
Level III - $142,000 - $172,000
Pay range for this role: $113,000 USD - $172,000 USD

Benefits

• Competitive total compensation package
• Comprehensive benefit package options include medical, dental, vision, life, and more
• 401k with company-match
• 3 weeks of paid time off each year
• 40 hours of sick time
• 12 annual company holidays

Why Join Us

• Innovative Environment: Work on cutting-edge technology that is shaping the future of defense and aerospace.
• Collaborative Culture: Join a team of passionate professionals dedicated to pushing the boundaries of what’s possible.
• Career Growth: Opportunities for professional development and career advancement.