Role & responsibilities

Role-Devops Engineer with AI ( Certified in Azure or Aws or Devops professionally)

Experience -3.5 years to 5years

Location-Hyderabad and Bangalore

Must Have skills -devops, Python, Bash, Aws,Kubernates, AI work flow deployment, LLM ,AWS Certified

If Interested share cv on [email protected] or Send cv on (phone hidden)

Preferred candidate profile

- Proven DevOps, platform, or deployment engineering experience shipping to production.
- Strong CI/CD and release-automation experience.
- Hands-on production experience with Docker and Kubernetes.
- Infrastructure as Code experience and strong AWS fluency.
- Scripting ability for automation (Python and/or Bash).
- Ability to integrate into a client's existing identity, security, and networking setup.
- A real understanding of how AI and LLM applications are deployed and run in production, including model serving and RAG/vector infrastructure.
- AWS Certified Solutions Architect Associate or AWS Certified DevOps Engineer Associate.

Key Responsibilities
- Package and deploy AI/LLM applications and agent workflows onto the client's AWS infrastructure.
- Build and maintain CI/CD pipelines that ship AI services safely and repeatably.
- Containerise services with Docker and run them on Kubernetes.
- Provision infrastructure as code with Terraform, integrating the required identity, security, and networking.
- Set up model and application serving, including AWS Bedrock integrations and vector database infrastructure.
- Add observability and cost tracking for AI workloads.




- Integrate AI solutions into existing legacy systems and regulated data environments.
- Automate repetitive deployment and operations tasks.
- Collaborate with client engineers over Teams, Slack, and email, and keep deployment runbooks current.

Required Qualifications
- Proven DevOps, platform, or deployment engineering experience shipping to production.
- Strong CI/CD and release-automation experience.
- Hands-on production experience with Docker and Kubernetes.
- Infrastructure as Code experience and robust AWS fluency.
- Scripting ability for automation (Python and/or Bash).
- Ability to integrate into a client's existing identity, security, and networking setup.
- A real understanding of how AI and LLM applications are deployed and run in production, including model serving and RAG/vector infrastructure.
- AWS Certified Solutions Architect Associate or AWS Certified DevOps Engineer – Associate.

Preferred Qualifications
- Deploying inside regulated environments with governance and change-management overhead.
- Enterprise AI or data platforms such as Databricks, Snowflake, or Palantir Foundry.
- MLOps tooling (MLflow, model registries, feature stores).
- Some SRE or reliability experience.
- Prior customer-facing or forward-deployed work.
- Certified Kubernetes Administrator (CKA) or a Terraform Associate certification.

Technical Skills & Tools
- Cloud (AWS): Bedrock, SageMaker, Lambda, ECS, EKS, Step Functions, S3, API Gateway, IAM, CloudWatch
- Containers & IaC: Docker, Kubernetes, Helm, Terraform, Ansible, CloudFormation

📌 Devops Engineer Associate (Bengaluru)
🏢 PwC
📍 Bengaluru