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

Cloud Soft Solutions; Mumbai; Hybrid; INR 1,400,000 - 3,000,000; Full time

Benefits offered by this job

ESOP / phantom-stock eligibility

Private medical for self + family

Hybrid 2–3 days in office

Sponsorted AWS/GCP certs

Job summary

Quantiphi in Mumbai seeks a mid-to-senior DevOps engineer to support its AI engineering practice. You will manage hybrid multi-cloud infrastructure across AWS and GCP, build production Kubernetes clusters, and implement secure CI/CD with CircleCI or GitHub Actions.

You will integrate MLOps platforms (Vertex AI/SageMaker) and cost-aware FinOps, write Terraform modules, and mentor peers. 3–8 years' experience required; INR 14-30 LPA; hybrid office model.

Qualifications

• 3–8 years of DevOps/platform engineering experience with hands-on exposure to AWS and GCP or strong AWS + GCP fluency.
• Production Kubernetes (EKS, GKE or both) at meaningful scale.
• Strong Terraform skills across AWS and GCP.
• End-to-end mastery of GitHub Actions, CircleCI, or GitLab CI.
• Hands-on with at least one MLOps platform or analytics warehouse (Vertex AI or SageMaker; BigQuery or Snowflake).
• Scripting in Python or Go. DevSecOps and FinOps awareness.

Responsibilities

• Build and operate multi-cloud infra across AWS and GCP including landing zones and identity federation.
• Stand up production Kubernetes clusters (EKS and/or GKE) and manage lifecycle and upgrades.
• Design CI/CD pipelines with reusable workflows and ArgoCD-driven GitOps deployments.
• Integrate MLOps stacks (Vertex AI/SageMaker) and feature stores; hand off prototypes to production.
• Author and review Terraform modules; consider cost and security implications.

Skills

AWS

GCP

Kubernetes

Terraform

CI/CD

MLOps

Python

Go

DevSecOps

FinOps

Tools

CircleCI

GitHub Actions

GitLab CI

Job description

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.

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

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.

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.