Own the organization’s DevOps architecture, cloud-native infrastructure, CI/CD ecosystem, infrastructure-as-code strategy, observability frameworks, and container orchestration platforms. Design scalable GCP/AWS environments, Kubernetes deployments, deployment and rollback strategies, security practices, and reusable automation. Partner with engineering, AI, testing, and product teams, govern tooling decisions, and maintain architectural documentation, runbooks, and reference architectures.
About Us :
Attentive.ai is a fast-growing vertical SaaS start-up, funded by Peak XV (Surge), InfoEdge, Insight Partners, Vertex Ventures, and Tenacity Ventures that provides innovative software solutions for the landscape, paving & construction industries in the United States. Our mission is to help businesses in this space improve their operations and grow their revenue through our simple & easy-to-use software platforms.
Position Description:
We are looking for a DevOps Engineer to join our engineering team and help us develop and expand various our internal pipelines and infrastructure As a DevOps Engineer at Attentive, you will be working closely with different engineering, AI, testing, and product teams to improve and expand their workflows and cloud resources. We offer an inspiring environment full of young people with a lot of ambition. You get the freedom to implement your own designs, solutions, and creativity
Roles & Responsibilities:
- Define and own the overall DevOps architecture, including CI/CD pipelines, infrastructure topology, deployment strategies, and platform engineering standards across the organization.
- Design and architect cloud-native infrastructure on GCP/AWS, ensuring high availability and scalability.
- Establish observability and reliability frameworks—knowledge of monitoring, alerting, logging, and tracing strategies using tools such as GCP Cloud Operations (Stackdriver), New Relic, ELK/OpenSearch, Prometheus, and Grafana.
- Design and implementation of Infrastructure as Code (IaC) strategies using Terraform, Ansible, and related tooling; enforce modularity, reusability, and governance across IaC repositories.
- Architect end-to-end CI/CD ecosystems—Design automated pipelines for building, testing, releasing, and rolling back applications; evaluate and standardise tooling (Jenkins, GitHub Actions, ArgoCD, etc.).
- Drive the containerization and orchestration strategy — Design and implement solutions using Docker and Kubernetes (GKE/EKS), including service mesh, ingress, secrets management, and multi-cluster topologies.
- Evaluate, recommend, and govern new tools, platforms, and technologies to continuously improve the DevOps ecosystem.
- Create and maintain architectural documentation, runbooks, decision records (ADRs), and reference architectures for infrastructure and platform services.
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Requirements:
- 4–8 years of overall experience in DevOps, Cloud Engineering, or Platform Engineering.
- Expertise in cloud platforms — GCP (preferred) and/or AWS, including networking (VPC, load balancing, DNS), IAM, security, and multi-region architecture.
- Strong proficiency in scripting and automation — Python, Groovy, and Bash; ability to build custom tooling and integrations.
- Knowledge of IaC — Terraform (module design, state management, workspaces), Ansible, and configuration management at scale.
- Extensive experience architecting CI/CD pipelines — Jenkins, GitHub Actions, ArgoCD or equivalent; including multi-environment promotion and rollback strategies.
- Advanced experience with containers and orchestration — Docker, Kubernetes (GKE/EKS), Helm, Kustomize, service mesh (Istio/Linkerd).
- Strong understanding of Linux systems, networking fundamentals, and distributed systems concepts.
- Experience designing and enforcing DevSecOps practices — shift-left security, vulnerability management.
- Working knowledge of developer platforms and tooling — GitHub/GitLab, JIRA, Confluence, artifact registries, and secret management (Vault, GCP Secret Manager).
Good to Have:
- Experience designing serverless architectures (Cloud Functions, Cloud Run).
- Familiarity with MLOps pipelines and tooling — Vertex AI, Kubeflow, MLflow, or equivalent; understanding of model training, serving, and monitoring workflows.
- Experience with GitOps methodologies and tools (ArgoCD, Flux)..
- Knowledge of AI tools OpenAI, Claude, Gemini
- Experience with multi-cloud or hybrid-cloud architectures.
- Relevant certifications such as GCP Professional Cloud Architect, AWS Solutions Architect, CKA/CKAD, or Terraform Associate/Professional
Attentive.ai New Delhi, Delhi, IND Office
New Delhi, India
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