Job Title: DevOps / Platform Engineer
Location: Bengaluru
Experience: 4–5 Years

About the Role

we are looking for a hands-on DevOps / Platform Engineer to establish and own our engineering infrastructure, CI/CD, deployment, and operational practices.

This is a foundational, build-from-scratch role. You will be responsible for designing and implementing the DevOps and Platform ecosystem rather than simply operating an existing infrastructure. The ideal candidate will work closely with Engineering and AI/ML teams to create scalable, secure, reliable, and developer-friendly infrastructure and deployment practices.

Key Responsibilities

1. Build CI/CD from the Ground Up

- Design and implement CI/CD pipelines for application services, APIs, AI services, and infrastructure.
- Automate build, testing, security scanning, packaging, and deployment processes.
- Establish standardized and reusable CI/CD pipelines for development teams.
- Implement automated deployments across Development, Staging, and Production environments.
- Integrate automated testing, code quality checks, security scans, and quality gates into pipelines.
- Establish Git-based development and release workflows.

2. Cloud & Infrastructure

- Design and establish cloud infrastructure and engineering environments from scratch.
- Set up appropriate Development, Testing, Staging, and Production environments.
- Implement infrastructure with a focus on scalability, reliability, security, and cost optimization.
- Establish infrastructure and deployment standards that can be reused across engineering teams.




- Automate infrastructure provisioning and operational processes wherever possible.

3. Containerization & Orchestration

- Containerize applications and services using Docker.
- Design and manage container-based deployment strategies.
- Work with Kubernetes / GKE or other container orchestration platforms.
- Develop reusable deployment configurations and patterns.
- Establish best practices for container security, resource management, and scalability.

4. AI / LLM Operations

- Work closely with AI/ML Engineers to establish reliable AI application deployment practices.
- Support deployment and operationalization of LLM-based applications and AI Agents.
- Understand and implement AI guardrails to ensure safe and controlled AI application behavior.
- Establish deployment and monitoring practices for AI services.
- Implement monitoring and observability for AI applications and supporting infrastructure.
- Good understanding of MCP (Model Context Protocol) and RAG (Retrieval-Augmented Generation) fundamentals will be an advantage.

5. Monitoring, Reliability & Operations

- Establish application and infrastructure monitoring from the ground up.
- Implement logging, metrics, alerting, and observability practices.




- Define operational standards for production systems.
- Troubleshoot deployment, infrastructure, and application issues.
- Improve system reliability, availability, performance, and operational efficiency.
- Establish incident response and production support practices.

Required Skills & Experience

- 4+ years of hands-on experience in DevOps, Platform Engineering, Cloud Engineering, or related roles.
- Strong experience building CI/CD pipelines from scratch.
- Strong knowledge of Git and modern software development/release workflows.
- Hands-on experience with at least one major cloud platform:

- AWS
- Azure
- GCP

Strong hands-on experience with Docker and containerization. Experience with Kubernetes, GKE, or another container orchestration platform. Robust scripting/programming skills using Python, Bash, or similar languages. Experience designing and managing cloud infrastructure and deployment environments. Good understanding of CI/CD, automation, networking, security, monitoring, and production operations. Ability to work independently and build DevOps/Platform practices from the ground up.

- Experience with observability tools such as Prometheus, Grafana, ELK, OpenTelemetry, or similar.
- Experience with cloud-native security and DevSecOps practices.

Key Focus Areas:
DevOps | Platform Engineering | CI/CD | Cloud | AWS/Azure/GCP | Docker | Kubernetes/GKE | Python/Bash | Infrastructure Automation | DevSecOps | AI/LLMOps | AI Agents | RAG | MCP | Monitoring & Observability

📌 DevOps Platform Engineer (Bengaluru)
🏢 S2V Automation
📍 Bengaluru