Senior DevOps Engineer

Senior DevOps Engineer

Hybrid 3 days/week onsite in Concord, CA

We are hiring two Senior DevOps Engineers to lead build, automation, and operations for modern cloud platforms with emphasis on AIOps and the model/ML development lifecycle. You will partner with Data/ML, Platform, and Security teams to deliver resilient and scalable systems that support AI-enabled applications and services.

Due to client requirements, applicants must be willing and able to work on a W2 basis. For our W2 consultants, we offer a great benefits package that includes medical, dental, and vision benefits, 401k with company matching, and life insurance.

Rate: $70.00 to $75.00/hr. W2

Responsibilities:

• Design and operate CI/CD pipelines for microservices, data services, and ML workloads.
• Implement Infrastructure as Code for cloud environments across AWS, Azure, or GCP.
• Build observability for metrics, logs, and traces, define SLOs and error budgets, and author automated runbooks.
• Drive reliability engineering practices including capacity planning, chaos testing, and incident response.
• Integrate AI/ML tooling to enhance monitoring, anomaly detection, auto-remediation, and incident prediction.
• Operationalize model monitoring and data drift detection with alerting aligned to business KPIs.
• Support end-to-end model lifecycle including data preparation, experiment tracking, model registry, CI/CD for ML, feature stores, and model serving.
• Implement governance for model lineage, approvals, versioning, reproducibility, and compliance controls.
• Embed security in pipelines with SAST/DAST, dependency scanning, and secrets management.
• Enforce RBAC, least privilege, policies-as-code, and auditable change management.
• Partner with Engineering, Data Science, and Product to align on architecture and SLAs.
• Mentor engineers and lead technical deep dives and incident postmortems.

Experience Requirements:

• 7 to 10+ years in DevOps, SRE, or Platform Engineering with production systems.
• Expertise with at least one major cloud provider such as AWS, Azure, or GCP and strong Terraform or equivalent IaC.
• Mastery of CI/CD tools such as GitHub Actions, GitLab CI, Azure DevOps, or Jenkins.
• Containerization and orchestration with Docker and Kubernetes at scale.
• Observability with Prometheus and Grafana, OpenTelemetry, ELK/EFK, Datadog, New Relic, or similar.
• Practical AIOps experience including anomaly detection, intelligent alerting, and automated runbooks or adjacent experience with willingness to lead AIOps adoption.
• Hands-on MDLC and MLOps including experiment tracking such as MLflow, model registry, model serving, feature stores, and model monitoring.
• Strong scripting and coding for automation using Python and Bash, with Go as a plus.
• Security-first mindset including secret management with Vault or KMS, container and image scanning, SBOM, and policy guardrails.
• Experience with data platforms such as Spark, Databricks, and Kafka and event-driven designs (preferred).
• GPU workload orchestration and cost and performance optimization for AI workloads (preferred).
• Governance and compliance experience such as SOC 2, ISO 27001, or HIPAA (preferred).
• FinOps exposure and cost observability in cloud environments (preferred).
• GitOps implementation with Argo CD or Flux (preferred).