About us:

Intuitive.AI is one of the fastest-growing (INC 5000, CRN) Cloud & SDx solution and services companies supporting enterprise customers on a global scale. Intuitive is an "Engineering Company" delivering measurable value and key business outcomes.

Intuitive Superpowers

- DataOps & AI/ML
- Cloud Native, AppSecOps, DevSecOps
- Cloud Migration & Transformation
- Cloud FinOps
- Cybersecurity (App/Data/Infra) & GRC
- SDx & Digital Workspace

We are proud to partner with some of the world's leading enterprises and serve 200+ customers across different industry verticals. We have achieved many milestones along the way, including being recognized as a top-10 fast-growth 150 IT company in the Americas by CRN in 2022 and being named one of America's fastest-growing private companies by INC 5000 in 2022. That’s not all!

Even CIO Review awarded us as the Most Promising Cloud Migration Company and Artificial Intelligence Solutions Provider in 2022.

About the job:

Title: Senior DevOps Engineer – Innovation Lab

Location: Bengaluru / Ahmedabad, India

Work Model: Hybrid

Employment Type: Full time

Note:

- Experience needed for Senior DevOps Engineers - 6+ years
- Experience needed for DevOps Engineers - 4+ years

About the Role

Intuitive.ai is looking for a Senior DevOps Lead to join our Innovation Lab and take hands-on ownership of DevOps, cloud infrastructure, CI/CD, DevSecOps, Kubernetes, and production deployments across our AI, GenAI, SaaS, and Application Modernization products.

The ideal candidate will have strong hands-on experience with AWS, Kubernetes, CI/CD, Infrastructure as Code, DevSecOps, and cloud operations, along with experience deploying Java, Python, GenAI, LLM, RAG, and Agentic AI applications.

This is a highly hands-on role requiring strong ownership, automation mindset, troubleshooting skills, and the ability to work closely with software engineers and product teams in a fast-paced startup/product engineering environment.

Key Responsibilities:

Cloud & Infrastructure:

- Deploy and operate applications primarily on AWS.
- Work with EC2, ECS, EKS, VPC, ALB/NLB, IAM, S3, RDS, CloudWatch, WAF, SSM, and KMS.
- Support deployments across Azure, GCP, Kubernetes, and Red Hat OpenShift.
- Provision and manage infrastructure using Infrastructure as Code.




- Manage cloud environments, configurations, backups, and production infrastructure.
- Troubleshoot infrastructure, networking, deployment, and production issues.

CI/CD & DevSecOps

- Build and maintain CI/CD pipelines for Java, Python, microservices, and AI applications.
- Work with GitHub Actions, Jenkins, GitLab CI, and/or Azure DevOps.
- Automate application build, testing, deployment, and rollback processes.
- Integrate security scanning into CI/CD pipelines.
- Work with SonarQube, Checkmarx, Black Duck, OWASP ZAP, container scanning, SAST, SCA, and DAST tools.
- Automate repetitive deployment and operational activities.

Containers & Kubernetes

- Build and manage Docker-based application deployments.
- Deploy and operate applications on Kubernetes, AWS EKS, ECS, and OpenShift.
- Work with Helm charts and Kubernetes configurations.
- Manage container registries such as AWS ECR.
- Troubleshoot container and Kubernetes production issues.

AI / GenAI Platform Deployment

- Deploy and operate GenAI, LLM, RAG, and Agentic AI applications.
- Support Python/FastAPI and Java/Spring Boot AI services.
- Deploy AI applications using AWS Bedrock, Azure OpenAI/Azure AI, and Google Vertex AI.
- Support AI agent orchestration platforms and services.
- Work with technologies such as Google ADK, LangGraph, LangChain, MCP, Neo4j, vector databases, and Langfuse.
- Support containerized AI workloads and GPU-based workloads where required.

Production Deployment & Operations

- Execute production deployments and releases.
- Implement rolling, blue-green, and canary deployment strategies.
- Configure automated health checks, smoke tests, rollback, and deployment validation.
- Troubleshoot application, infrastructure, networking, and cloud issues.
- Participate in production support and root-cause analysis.
- Support disaster recovery, backup, and availability requirements.

Platform Monitoring





- Implement and maintain application and infrastructure monitoring.
- Work with OpenTelemetry, Prometheus, Grafana, Loki, ELK/OpenSearch, and CloudWatch.
- Support centralized logging, metrics, and tracing.
- Monitor application health, infrastructure performance, and deployment issues.

Collaboration & Technical Leadership

- Work closely with software engineers, AI engineers, architects, and product teams.
- Help development teams adopt standardized CI/CD and deployment practices.
- Review deployment configurations and identify opportunities for automation.
- Mentor junior DevOps engineers and provide hands-on technical guidance.
- Take ownership of DevOps activities across multiple Innovation Lab products.
- Help build reusable CI/CD pipelines, deployment templates, and automation scripts.

Required Technical Skills

- Cloud: Strong AWS experience with EC2, ECS, EKS, VPC, IAM, S3, RDS, ALB/NLB, CloudWatch; working knowledge of Azure/GCP.
- DevOps & CI/CD: Docker, Kubernetes/EKS, Helm, GitHub Actions, Jenkins, GitLab CI, or Azure DevOps.
- Infrastructure as Code: Terraform; Pulumi/CloudFormation is a plus.
- DevSecOps: SonarQube, Checkmarx, Black Duck, OWASP ZAP, SAST/SCA/DAST, and container security.
- Observability: OpenTelemetry, Prometheus, Grafana, Loki, ELK/OpenSearch, and CloudWatch.
- AI/GenAI: Deployment of LLM, RAG, AI Agent, and Python/FastAPI applications; exposure to Bedrock, Azure OpenAI, Vertex AI, vector databases, and Neo4j is a plus.
- Application Platforms: Java/Spring Boot, Python/FastAPI, microservices, REST APIs, and RabbitMQ/Kafka or similar messaging platforms.
- Production Engineering: Automated deployments, rollback, smoke testing, blue-green/canary deployments, and performance testing using k6, JMeter, or Gatling.

Preferred Experience

- Experience supporting SaaS, AI-powered, GenAI, or enterprise modernization products.
- Experience deploying applications across AWS and Kubernetes.
- Experience with AWS Bedrock, Azure OpenAI, or Google Vertex AI.
- Experience with AI agent and RAG application deployments.
- Experience with cloud cost optimization is a plus.
- Experience with AWS Marketplace or AWS Partner programs is a plus.
- Experience in security and compliance environments is a plus.

📌 Senior DevOps Engineer – Innovation Lab (Bengaluru)
🏢 Intuitive.ai
📍 Bengaluru