Forward Deployed Engineer

Wipro; Hyderabad, Chennai, Bengaluru; Hybrid; INR 2,000,000 - 4,000,000; Full time

Job summary

Wipro in India is seeking an experienced AI/GenAI engineer to design, develop, and deploy AI agents using LangChain, LangGraph, and agent frameworks. You will build agent workflows for automation, incident response, and reliability engineering across cloud platforms.

You will deploy AI solutions on Azure, AWS, and GCP, orchestrate CI/CD pipelines, integrate observability, and collaborate with DevOps, SRE, Security, and Platform teams to deliver production-ready AI capabilities.

Qualifications

• 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.
• Strong experience with one or more Hyperscalers: Azure, AWS, or GCP.
• Hands-on experience with Kubernetes, 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.

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.

Skills

Python

LangChain

LangGraph

Agentic AI

LLM tech

Azure

AWS

GCP

Kubernetes

Docker

Terraform

CI/CD

GitHub Actions

Azure DevOps

Jenkins

IaC

Grafana

Prometheus

OpenTelemetry

Splunk

Datadog

Tool Calling

Agent Orchestration

Structured Outputs

RAG

Vector DB

Observability

DevOps

SRE

Security

Tools

Docker

Kubernetes

Terraform

GitHub Actions

Azure DevOps

Jenkins

CI/CD

IaC

Job description

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
• Strong 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.