DevSecOps/MLOps Engineer (Kubernetes, AWS, CI/CD)

Top 3 reasons to join us

• Competitive Compensation
• Cutting-Edge Technology, AI Security
• Global Environment

Job description

• Define and execute the end-to-end DevSecOps / MLOps strategy (CI/CD, infrastructure, security, observability).
• Architect, deploy, and operate cloud infrastructure (AWS) with focus on scalability, high availability (HA), and security.
• Design and optimize CI/CD pipelines using Jenkins, GitLab CI, ArgoCD.
• Standardize and manage Kubernetes environments (EKS / on-prem), including GPU workloads, networking, ingress, and autoscaling.
• Implement Infrastructure as Code (Terraform, Ansible) for automated provisioning and operations.
• Build and maintain monitoring & observability systems (Prometheus, ELK/OpenSearch, Datadog).
• Drive DevSecOps best practices: SAST, DAST, container security, SBOM.
• Optimize infrastructure cost following FinOps principles.
• Collaborate closely with Engineering, AI, Data, and Security teams.
• Develop runbooks, disaster recovery (DR) plans, and design high availability architectures.

Your skills and experience

Requirements

• Bachelor’s degree in computer science, IT, or related field.
• 5+ years in DevOps / SRE / Platform Engineering.
• Proven experience operating large-scale production systems (AI/GPU workloads is a strong advantage).

Technical Skills

• Cloud & Infrastructure: Strong expertise in AWS / Azure / GCP; solid understanding of HA, DR, multi-region architecture.
• Containers & Orchestration: Hands-on experience with Docker & Kubernetes (EKS/AKS/on-prem); strong understanding of networking (CNI, ingress); service mesh is a plus.
• CI/CD: Experience with Jenkins, GitLab CI, ArgoCD; ability to design full pipelines (build → scan → deploy → rollback).
• Infrastructure as Code: Strong hands-on with Terraform (required); Ansible/Helm is a plus.
• Observability: Experience with Prometheus, Grafana, ELK/OpenSearch, Datadog; understanding of APM & distributed tracing (OpenTelemetry is a plus).
• Security: Solid knowledge of DevSecOps practices (SAST, DAST, container security); experience with tools like Trivy, Dependency-Track, DefectDojo.
• Experience building end-to-end MLOps platforms
• Familiarity with tools such as KServe, MLflow, Airflow, DVC.
• Understanding of model reproducibility, GPU workload automation, and advanced deployment patterns (canary, A/B testing, shadow traffic).

Preferred

• Experience building Internal Developer Platform (IDP).
• Exposure to AI/LLM in DevOps (AIOps, AI Agents).
• Knowledge of Kafka, ClickHouse, or data pipelines.
• FinOps mindset and cost optimization experience.
• Relevant certifications (AWS / Azure / GCP, CKA / CKAD).

Why you'll love working here

• Work on cutting-edge platforms at the intersection of Cloud, AI, and Cybersecurity.
• Lead impactful initiatives with high ownership and real business impact.
• Opportunity to build and scale modern DevSecOps/MLOps platforms from the ground up.
• Dynamic, fast-growing environment with top-tier engineering talent.