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Forward Deployed Engineer (AI, Hyperscale Cloud & DevOps)

  • Source: Naukri
  • Varite
  • On-site
  • Bengaluru
  • Full-Time
  • Mid level

Job Description

Please apply only if you are available to attend the Face-to-Face Interview Drive on 31st October 2026 at one of the following locations:

Bangalore
Hyderabad
Pune
Chennai

Forward Deployed Engineer (AI, Hyperscale Cloud & DevOps)

Role Summary

We are seeking a hands-on Forward Deployed Engineer (FDE) with expertise in Generative AI, Hyperscaler Cloud Platforms, DevOps, and Platform Engineering. The role involves designing, deploying, integrating, and operationalizing AI agents and cloud-native solutions across enterprise environments while ensuring reliability, scalability, security, and operational excellence.

Key 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.

Required Skills & Experience

  • 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.

Preferred Skills

  • Multi-cloud architecture and deployment experience across Azure, AWS, and GCP.
  • Experience with AI Reliability Engineering, LLMOps, MCP, Agent Gateways, and Responsible AI practices.
  • Exposure to .NET or Java application development.
  • Experience working in enterprise or regulated environments.
  • Certifications in Azure, AWS, GCP, Kubernetes, AI Engineering, or DevOps.

Skills

  • microsoft-azure
  • amazon-web-services
  • google-cloud-platform
  • Kubernetes
  • guardrails
  • Python
  • LangChain
  • LangGraph
  • Docker
  • Terraform
  • Github
  • github-actions
  • azure-devops
  • Jenkins
  • Grafana
  • Prometheus
  • opentelemetry
  • splunk
  • dynatrace
  • datadog
  • dot-net
  • Java

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