5+ years of experience in DevOps, SRE, platform, or infrastructure engineering with ownership of production systems
Hands-on experience with infrastructure as code tools like Terraform or Ansible in production
Strong Linux expertise and proficiency in scripting languages such as Python and Bash
Experience with observability systems for metrics, logging, and tracing
Production experience with containers and Kubernetes, including deployment and troubleshooting
Strong understanding of security best practices and threat modeling
Proven ability to independently solve ambiguous technical challenges
Responsibilities
Build and manage infrastructure as code across AWS and on-prem environments
Own and optimize CI/CD pipelines for robotics software and ML workloads
Design and maintain observability systems to monitor performance and reliability
Deploy and operate Kubernetes clusters across cloud and edge environments
Implement security best practices, including secrets management and vulnerability scanning
Define SLOs and lead incident response for continuous improvements
Automate repetitive tasks and streamline infrastructure operations
Collaborate with robotics and ML teams to solve technical challenges
Benefits
Autonomy to take ownership of projects
Opportunity to work with cutting-edge robotics technology
Data-driven decision-making culture
Collaborative environment with cross-functional teams
Potential for professional growth in a small team setting
Full Job Description
About the Role
As a DevOps Engineer at Maven Robotics, you will build and run the infrastructure that ships, observes, and secures a fleet of industrial robots and the platform behind them. This is a generalist role that spans DevOps, SRE, and security. You will work across AWS, on-prem and edge Kubernetes, CI/CD, and the telemetry that tells us how all of it is actually behaving.
As an early member of our small infrastructure team, you'll have the autonomy to take ownership, solve complex problems, and drive solutions from concept to execution. We take a data-driven approach to decision-making, so you'll build the metrics and insights needed to guide your recommendations. When robotics or ML engineers bring challenging requests, you'll approach them with a solutions-oriented mindset, finding ways to make things happen safely and effectively rather than focusing on limitations.
What You'll Do
Build and manage infrastructure as code (Terraform, Ansible) across AWS and on-prem environments, ensuring scalability, reliability, and reproducibility
Own and optimize CI/CD pipelines (GitLab, GitHub Actions) for robotics software, ML workloads, and platform services
Design and maintain observability systems (OpenTelemetry, Prometheus, Grafana) to monitor performance, reliability, capacity, and costs
Deploy and operate Kubernetes clusters across cloud and edge environments, supporting robotic systems and deployments
Implement security best practices, including secrets management, IAM, mTLS, Linux hardening, and vulnerability scanning
Define SLOs, lead incident response, and drive continuous improvements through root cause analysis and postmortems
Automate repetitive tasks, streamline infrastructure operations, and improve engineering efficiency
Collaborate with robotics, ML, and field engineering teams to solve technical challenges, improve developer experience, and document scalable solutions
What We're Looking For
5+ years of experience in DevOps, SRE, platform, or infrastructure engineering with ownership of production systems
Hands-on experience building and maintaining infrastructure as code (Terraform, Ansible, or equivalent) in production environments
Strong Linux expertise and proficiency in scripting languages such as Python and Bash
Experience designing and managing observability systems, including metrics, logging, and tracing, to drive data-informed decisions
Production experience with containers and Kubernetes, including deployment, networking, storage, upgrades, and troubleshooting
Strong understanding of security best practices, including threat modeling, least-privilege access, secrets management, and implementing security controls
Proven ability to independently solve ambiguous technical challenges, take ownership, and deliver production-ready solutions
Proactive, solutions-oriented mindset with strong communication skills and the ability to navigate tradeoffs and collaborate across teams
Nice to Have
Experience with edge or on-prem infrastructure supporting robotics, industrial systems, or remote environments with limited connectivity
Familiarity with Kubernetes distributions (Talos or similar) and GitOps tools such as Argo CD or Flux
Knowledge of ML infrastructure, including distributed computing, cloud storage, data pipelines, and large-scale artifact management
Strong networking fundamentals, including VLANs, VPNs, firewalls, and network segmentation across IT/OT environments
Contributions to open-source infrastructure projects or hands-on experience building and maintaining a homelab
