DevOps, MLOps & Security Engineering Lead

Responsibilities

• Own the design and governance of CI/CD pipelines — including automated testing, SAST/DAST scanning, dependency checks, and secrets detection.
• Lead infrastructure-as-code and container orchestration practices, and drive automation initiatives that reduce manual effort and improve consistency at scale.
• Apply engineering rigor to ML training pipelines, model serving infrastructure, and data supply chains.
• Design and manage the AI infrastructure layer — including GPU/compute resource provisioning, model registry operations, experiment tracking, and inference scaling — across AWS and GCP.
• Ensure AI systems are built, deployed, and monitored to the same reliability and security standards as core product services.
• Lead end-to-end security across cloud, infrastructure, and product — spanning cloud posture management, API protection, runtime security, network segmentation, and secrets management across AWS and GCP environments.
• Define and enforce security policies, standards, and best practices that balance delivery speed with a strong compliance posture.
• Anticipate operational risks, drive preventative measures, and lead rapid incident response across environments.
• Translate security and engineering requirements into actionable roadmaps.
• Define and track KPIs that demonstrate delivery effectiveness and inform prioritization.
• Act as a trusted security advisor to engineering squads and leadership alike.

• A proven engineering leader with hands‑on depth in Dev Sec Ops , capable of growing and inspiring a high‑performing team
• Strong hands‑on knowledge of AWS and GCP — including compute, networking, IAM, managed Kubernetes (EKS/GKE), cloud‑native security tooling, and cost‑efficient resource management across both platforms
• Deep experience managing AI infrastructure — GPU/TPU provisioning, distributed training environments, model serving platforms (e.g. Sage Maker, Vertex AI), and inference optimization at scale
• Strong knowledge of cloud security, infrastructure security, and modern CI/CD platforms across hybrid, multi‑cloud environments
• Proficient in scripting and development — Python, Bash, Go, or Java
• A confident communicator who can translate priorities clearly across developers, stakeholders, and executives
• Familiarity with AI‑assisted security — threat detection, anomaly detection, intelligent vulnerability triage — is a strong advantage
• Background in Computer Science, Information Security, or equivalent practical experience