Live opening · Posted 27 days ago
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Description supplied by the original job listing.
Responsibilities:
Lead and mentor a small team of DevOps, MLOps, and cloud engineers; promote high performance, knowledge sharing, and continuous learning.
Architect and maintain scalable GCP infrastructure for AI agentic workloads (Vertex AI, GKE, Cloud Run, Cloud Functions, Artefact Registry, etc. )
Own DevOps and MLOps pipelines, including:
CI/CD with Google Cloud Build (primary) and integration/experience with Jenkins for hybrid/legacy workflows.
Artefact management using Artefact Registry (primary) with exposure to Nexus Repository for proxying or migration scenarios.
IaC (Terraform preferred), container orchestration, and Python scripting/automation for custom tooling, Glue jobs, or pipeline extensions.
Lead API endpoint security strategy, leveraging the following:
Apigee for enterprise-grade API management, policy enforcement, quotas, monetisation (if applicable), advanced security, and analytics.
Complementary GCP-native tools: Identity-Aware Proxy (IAP), Cloud Armour (WAF/DDoS), IAM least-privilege, OAuth 2.0/JWT/mTLS, Secret Manager, and VPC Service Controls.
Zero-trust/BeyondCorp principles and threat protection for AI agent communications and customer-facing APIs.
Champion FinOps practices on GCP:
Implement cost monitoring (Cloud Billing, FinOps Hub), optimisation recommendations (Recommender, Active Assist), commitment-based discounts (CUDs), budget alerts, and idle resource cleanup.
Drive cost allocation, forecasting, and cross-team accountability for high-cost AI workloads (e. g., model training/inference).
Collaborate with AI/ML engineers to productionise agentic workflows with secure, governed access to models/data.
Ensure high observability (Cloud Operations Suite, Prometheus/Grafana), resilience, and SRE practices (incident response and post-mortems).
Establish cloud governance, compliance, and disaster recovery aligned with business needs.
Requirements:
8+ years in DevOps, cloud engineering, or infrastructure roles, with 4+ years of deep hands-on Google Cloud Platform (GCP).
Proven people leadership (5+ reports) in agile/fast-paced environments.
Strong expertise securing APIs/services on GCP, preferably with Apigee (enterprise API management, policies, and analytics) alongside IAP, Cloud Armour, IAM, and mTLS.
Hands-on experience with:
CI/CD: Google Cloud Build + integration with Jenkins.
Artefact management: Artefact Registry + familiarity with Nexus Repository.
GKE/Cloud Run, monitoring/logging.
Python for automation, scripting, and tooling in DevOps/MLOps contexts.
Solid understanding of networking (VPC and Private Service Connect), security, and compliance.
Experience with AI/ML platforms (Vertex AI, Agent Builder) and MLOps for agentic systems is highly desirable.
Preferred Skills:
Google Cloud certifications: Professional DevOps Engineer, Cloud Architect, Cloud Security Engineer (Apigee-related knowledge is a plus).
FinOps experience or certification.
Familiarity with GCP FinOps Hub, Recommender, and commitment management.
Exposure to agentic AI patterns (multi-agent orchestration, RAG) and their infra requirements.
Experience in high-security or regulated environments.
Experience
12-16 yrs
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