Devops Engineer Associate

About this job

Role & responsibilities

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

Location-Hyderabad and Bangalore

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

If Interested share cv on bommakanti.sai.vaidehi@pwc.com or Send cv on 6304776536

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 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.

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