Detailed JD Below.

Forward Deployed Engineer (AI, Hyperscaler 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.

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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.

Behavioral Attributes

- Strong ownership mindset with a "get things done" attitude.
- Excellent problem-solving and multitasking abilities.
- Ability to work directly with client and platform teams.
- Curious, adaptable, and eager to learn emerging AI and hyperscaler technologies

Advantages:

- Health insurance

Work Location: In person

📌 AI Engineer (Bengaluru)
🏢 Wipro
📍 Bengaluru