DevOps Engineer (AWS, GCP, Kubernetes) — Quantiphi · Mumbai

About the role

Mid / senior DevOps engineer for Quantiphi's AI engineering practice — hybrid AWS + GCP infrastructure, Kubernetes, MLOps integration with Vertex AI / SageMaker. 3-8 years, hybrid Mumbai, INR 14-30 LPA band.

About this role and the team at Quantiphi. Mid / senior DevOps engineer for Quantiphi's AI engineering practice — hybrid AWS + GCP infrastructure, Kubernetes, MLOps integration with Vertex AI / SageMaker. 3-8 years, hybrid Mumbai, INR 14-30 LPA band. This listing on cloudsoftsol.com is curated for engineers in India who are actively interviewing for senior cloud and DevOps roles. The role is permanent / full-time, hybrid, and the salary band reflects market rates in Mumbai (Bangalore option) as of mid-2026. If you are seeking a multi-year career platform rather than a stop-gap, this listing rewards depth — read the responsibilities and requirements below carefully and tailor your application to the specifics. Cloudsoft Solutions runs the leading AWS, Azure, GCP, DevOps, Citrix and VMware training and placement programmes in Hyderabad and Bangalore — if you would like coaching for this exact role, mock interviews, resume review or salary-negotiation help, please contact us at info@cloudsoftsol.com. We do not charge candidates a fee for placement assistance; companies sponsor our involvement.

Responsibilities

Build and operate the multi-cloud infrastructure that powers Quantiphi's AI engineering and analytics engagements across AWS and GCP — landing zones, identity federation, secrets, and unified observability. Stand up production Kubernetes (EKS and GKE) clusters with platform add-ons (NGINX Ingress, cert-manager, External Secrets Operator, AWS Load Balancer Controller / GKE Ingress) and operate them through cluster lifecycle and Kubernetes minor-version upgrades. Design CI/CD pipelines in CircleCI and GitHub Actions, with reusable workflows, image scanning, signed-artefact promotion, and ArgoCD-driven GitOps deployment into the clusters. Integrate with the MLOps stack — Vertex AI for GCP, SageMaker for AWS, Snowflake / BigQuery as feature stores — and own the hand-off between data-science prototypes and production-grade serving. Author Terraform modules covering AWS and GCP, version them in a shared internal registry, and review other engineers' plans for cost and security implications before they land in production. Implement DevSecOps in CI: SAST (SonarCloud), SCA (Snyk / Dependabot), IaC scanning (Checkov), secret-scanning (gitleaks), and image scanning (Trivy). Gate higher environments on clean reports. Drive FinOps practices: cost-attribution tags, anomaly detection, Reserved Instance / CUD modelling, and monthly cost-review meetings with engagement leads. Drive at least one major cost-reduction initiative each quarter. Run blameless post-incident reviews, mentor junior engineers, and contribute to Quantiphi's internal multi-cloud playbook.

Requirements & qualifications

3-8 years of DevOps / Platform engineering experience with hands-on production exposure to both AWS and GCP, or strong AWS plus a credible GCP fluency. Production Kubernetes (EKS, GKE or both) at meaningful scale. Strong Terraform skills; comfortable with provider-specific quirks across AWS and GCP. At least one of: GitHub Actions, CircleCI, or GitLab CI mastered end-to-end. Hands-on with at least one MLOps platform (Vertex AI or SageMaker) or one analytics warehouse (BigQuery or Snowflake). Working scripting in Python or Go. DevSecOps and FinOps awareness; comfortable presenting findings in client-facing meetings. Cloud certifications across AWS + GCP preferred.

Why this role in 2026

Quantiphi is one of the most respected pure-play AI engineering firms globally — the kind of consulting work where the engineering quality bar genuinely shows up in the deliverable. The DevOps team's mandate is unusually broad: you ship infrastructure across two clouds, integrate it with bleeding-edge ML platforms, and present trade-offs directly to enterprise architects on the client side.

Application tips

Apply via the careers portal or email careers@quantiphi.com with subject "DevOps Engineer (AWS / GCP) — Mumbai — <name>". Highlight any direct MLOps or data-platform exposure prominently — Quantiphi specifically valuates that combination.

Interview preparation

Four rounds: recruiter, technical screen on AWS + GCP + Kubernetes, hands-on (Terraform module + a quick GitHub Actions workflow), and a hiring-manager round on culture and consulting communication. Practice presenting cost / security trade-offs concisely.

Career growth

Track: Cloud Engineer → Senior Cloud Engineer → Cloud Architect → Engineering Manager. Quantiphi has a strong culture of internal promotion and many of its current cloud architects started as mid-level engineers within 3-4 years.

Company & benefits

INR 14-30 LPA plus 8-12% bonus. ESOP / phantom-stock eligibility for senior individual contributors. Comprehensive private medical for self + family. Hybrid 2-3 days office. Sponsored AWS and GCP certifications. Generous learning budget for conferences and online subscriptions.