Senior DevOps Engineer
Maven AGI•Boston, MA
•$165,000 - $190,000
About The Position
Maven AGI is seeking a Senior DevOps Engineer to be responsible for the design, building, and operation of production systems across various environments including cloud providers, Kubernetes clusters, and on-premises setups. The role involves managing CI/CD pipelines to ensure the platform's reliable scaling for enterprise customers with specific deployment and security needs. This is a critical position that directly influences platform availability, developer efficiency, and customer trust.
Requirements
- 3-7 years of professional DevOps/SRE/Infrastructure experience
- Deep expertise with Kubernetes in production (AKS, EKS, or GKE)
- Strong infrastructure-as-code skills (Pulumi, Terraform, or Bicep)
- Experience operating CI/CD systems (GitHub Actions, ArgoCD, or Jenkins)
- Proficiency in at least one scripting/programming language (Python, Go, TypeScript, or Bash)
- Solid understanding of IaaS providers, networking, DNS, load balancing, and TLS
- Experience with monitoring and observability stacks (Datadog, Prometheus, Grafana, or similar)
- Experience with multi-cloud or hybrid (cloud + on-prem) deployments
- Strong communication and cross-team collaboration skills
- Organized, great attention to detail, comfortable operating in a ticketing environment
- Thrives in fast-paced startup environments
Nice To Haves
- Experience with GPU infrastructure and ML/LLM serving workloads (vLLM, TEI)
- Familiarity with Temporal or other workflow orchestration systems
- Security and compliance background (SOC 2, HIPAA, GDPR)
- Cost optimization experience at scale
Responsibilities
- Design, implement, and maintain both cloud and on-premise infrastructure (Azure, AWS, datacenter) using infrastructure-as-code (Pulumi, Bicep, Terraform)
- Own Kubernetes cluster operations: deployments, scaling, monitoring, and incident response
- Build and optimize CI/CD pipelines for a large-scale monorepo
- Implement observability across services (metrics, logging, tracing, alerting)
- Drive reliability practices: SLOs, capacity planning, disaster recovery, and runbook development
- Operationalize and scale enterprise AI deployments on-premise, including GPU resource orchestration, model inference performance tuning, and high-concurrency platform management.
- Collaborate with engineering teams to improve developer experience and deployment velocity
- Manage secrets, access controls, and infrastructure security posture
- Evaluate and adopt new tooling to reduce operational toil
Benefits
- Competitive salary
- Comprehensive benefits
- Meaningful equity stakes
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
