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
