DevOps Engineer

Location: Bangalore

Experience: 2–5 Years

About the Company – Crest.ai

Crest.ai is building the AI brain for supply chains, where LLMs meet supply chain intelligence.

The platform combines machine learning, large language models, and real-time analytics to help companies:

1. Predict demand
2. Automate procurement
3. Optimize distribution

With features like natural language forecasting, explainability layers, and AI-driven procurement workflows, Crest.ai enables businesses to make faster, smarter, and more resilient supply chain decisions.

Role Overview

We are looking for a DevOps Engineer with 2–5 years of experience in managing modern cloud-native infrastructure.

The role involves working with Kubernetes, AWS or GCP, CI/CD pipelines, automation, networking, and observability tools to ensure our systems are secure, scalable, and reliable.

This role is ideal for someone passionate about solving complex infrastructure challenges and enabling high-velocity engineering teams.

Key Responsibilities

Infrastructure & Kubernetes

1. Design, deploy, and manage Kubernetes clusters (EKS or GKE) for scalable and reliable workloads.

Cloud Engineering

1. Build and optimize infrastructure across AWS or GCP including VPC, networking, IAM, and storage.

Automation & CI/CD

1. Implement Infrastructure as Code (IaC) using Terraform, Helm, and Ansible.
2. Develop and maintain CI/CD pipelines for automated deployments.

Security & Observability

1. Implement system security best practices and secrets management.
2. Build monitoring and logging stacks using Prometheus, Grafana, Loki, ELK or EFK, OpenTelemetry.

Reliability & Scaling

1. Design resilient infrastructure with auto-scaling, fault tolerance, and disaster recovery strategies.

Cross-Team Collaboration

1. Work closely with developers, QA, and product teams to streamline releases and maintain uptime.

Tooling & Automation

1. Build internal tools and automation scripts using Python, Go, or Bash.

Required Skills & Experience

Kubernetes

1. Hands-on experience managing Kubernetes (EKS or GKE) in production environments.

Cloud Platforms

1. Strong experience with AWS or GCP services (EC2, S3, RDS, IAM, VPC, etc.).

Networking

1. Strong understanding of TCP/IP, DNS, VPNs, routing, firewalls, SSL/TLS, and load balancing.

Infrastructure as Code

1. Experience with Terraform, Helm, and Ansible.

CI/CD

1. Experience building pipelines using GitHub Actions, GitLab CI, or Jenkins.

Monitoring & Observability

1. Experience with Prometheus, Grafana, Loki, OpenTelemetry, or Jaeger.

Databases & Messaging

1. Familiarity with Postgres, MongoDB, Redis, Kafka, and RabbitMQ.

Scripting

1. Strong scripting skills in Bash, Python, or Go.

Operating Systems & Security

1. Strong understanding of Linux systems and infrastructure security practices.