Forward Deployed Engineer

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.