Forward Deployed Engineer (AI, Hyperscale Cloud & DevOps)

Role & responsibilities

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.

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