We are looking for a DevOps Engineer to build and run cloud infrastructure, CI/CD, and observability for Data and AI teams in a PCI-compliant environment.
The mandatory requirements are 4+ years of DevOps, SRE or platform engineering experience, CI/CD and infrastructure-as-code, Kubernetes and cloud platforms, and cloud security and compliance in PCI-regulated environments.
RECRUITMENT PROCESS
- 1. Application — Share a few details about your experience and background.
- 2. Coding Challenge — If applicable, complete it in the coding language you are most comfortable with.
- 3. Video Interview — Record a short video introduction in English.
- 4. Technical Interview or Hiring Manager Interview — Discuss your experience and fit for the role.
- 5. Offer — If it’s a match, you’ll receive an offer.
WHAT YOU'LL GAIN
- Remote work — Work from where you feel most productive.
- Local presence in India — Work in a structured and compliant environment aligned with Indian regulations.
- Competitive compensation in INR — Receive compensation in INR, plus support for learning, education, and wellness.
- Exciting projects — Work with modern technologies for global clients and fast-growing companies.
MUST HAVES
- 4+ years of professional DevOps, SRE or platform-engineering experience operating production services.
- 3+ years of hands‑on experience building CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI or CircleCI) and managing infrastructure as code (Terraform, Pulumi or CloudFormation).
- Working knowledge of Kubernetes (EKS, AKS or GKE) and container tooling (Docker, Helm, ArgoCD or Flux).
- Strong scripting skills in Python, Bash or Go; solid SQL skills and strong comfort with at least one cloud platform (AWS, Azure or GCP).
- Hands‑on experience with observability stacks: New Relic, Prometheus, Grafana, OpenTelemetry, ELK or Datadog.
- Solid understanding of cloud security and compliance practices, particularly in PCI-compliant or regulated environments.
- Proven ability to work independently and within a team, managing priorities across concurrent projects and time zones, including on‑call rotations.
- Strong written and verbal communication skills; able to work effectively with both technical and non-technical stakeholders.
NICE TO HAVES
- Experience operating Dataiku DSS, Snowflake, or other large-scale data and analytics platforms in production.
- Experience with service meshes (Istio, Linkerd), API gateways, and zero-trust networking.
- Experience with policy-as-code (OPA / Rego, Checkov, tfsec) and supply‑chain security (SBOM, Sigstore).
- Experience with FinOps practices and cloud cost optimization.
- Experience supporting ML or LLM workloads — GPU scheduling, model‑serving infra, vector databases or LangSmith / Langfuse.
- Experience with database administration / reliability for PostgreSQL, MySQL or Snowflake.
- Experience in loyalty, martech, adtech or a comparable data-rich B2B domain.
WHAT YOU WILL DO
- Strategy, Roadmap & Vision – build the roadmap for devops and observability in Data & AI teams.
- Design and build cloud infrastructure as code with Terraform (or Pulumi / CloudFormation), packaging reusable modules for AWS, Azure or GCP, and own CI/CD pipelines in GitHub Actions, Jenkins or GitLab CI.
- Operate Kubernetes clusters (EKS, AKS or GKE) and container workloads with LENS, Helm, ArgoCD or Flux — including autoscaling, ingress, secrets and policy.
- Build observability with Prometheus, Grafana, OpenTelemetry, ELK or Datadog — metrics, logs, traces, dashboards and SLO-driven alerting.
- Implement security and compliance controls: IAM, SSO, secrets management (Vault / KMS), vulnerability scanning, policy-as-code (OPA, Checkov) and PCI-aware patterns.
- Lead incident response — on-call, runbooks, blameless post-mortems, and continuous reliability work to drive down MTTR and toil.
- Partner with developers on local dev experience, golden paths, internal platform tooling and developer self‑service, while helping shape internal platform standards and sharing knowledge across the India and U.S. teams.
- Participate in a collaborative DevOps environment, working closely with developers, AI engineers, QA, DBAs and product partners across environments.