Role & responsibilities

- Design, develop, and deploy AI/GenAI agents using Agentic AI frameworks and LLM technologies.
- Build and operationalize agent workflows for automation, incident response, RCA, deployment validation, and reliability engineering.
- Deploy and manage AI solutions across hyperscaler cloud platforms (Azure, AWS, GCP) and Kubernetes environments.
- Integrate agents with CI/CD pipelines, observability tools, ITSM platforms, code repositories, and enterprise systems.
- Develop reusable APIs, connectors, prompt templates, and automation frameworks.
- Implement AI governance controls including guardrails, access controls, audit logging, monitoring, cost optimization, and rollback mechanisms.
- Own deployment, troubleshooting, observability, and continuous improvement of AI agent platforms.
- Collaborate with DevOps, SRE, Security, Platform, and Engineering teams to deliver production-ready solutions.

Preferred candidate profile

- 5+ years of experience in Software Engineering, Cloud Engineering, DevOps, SRE, AI/ML Engineering,



or related roles.
- Strong programming skills in Python with experience building AI/GenAI applications.
- Hands-on experience with LangChain, LangGraph, Agentic AI frameworks, and LLM technologies.
- Experience deploying AI/GenAI solutions in production environments.
- Strong understanding of:
- Prompt Engineering
- RAG
- Vector Databases
- Tool Calling
- Agent Orchestration
- Structured Outputs

- Robust experience with one or more Hyperscalers: Azure, AWS, or GCP.
- Hands-on experience with:

- Kubernetes (AKS/EKS/GKE)
- Docker
- Terraform
- GitHub Actions / Azure DevOps / Jenkins
- CI/CD and Infrastructure as Code (IaC)

- Experience with observability and monitoring tools such as Grafana, Prometheus, OpenTelemetry, Splunk, Dynatrace, or Datadog.
- Understanding of DevOps, SRE, cloud reliability, security, and operational best practices.

📌 Forward Deployed Engineer (Hyderabad)
🏢 Wipro
📍 Hyderabad