Forward Deployed Engineer

Candidate should have 10 to 15years of experience.

 Experience building GenAI applications, including RAG, multi-agent systems, fine-

tuning, etc., with tools such as LangChain, LangGraph etc.

 Clear understanding of Model Context Protocols, A2A Protocols, Agent Developeer

Kit and working experience with LLMs

 Expertise in deploying production grade GenAI solutions, including evaluation and

optimizations; Machine Learning deployments on AWS, Azure or GCP

 Extensive hands-on data science experience, leveraging machine learning and data

science tools (i.e., pandas, scikit-learn, PyTorch, etc.)

 Experience with DevOps tools: Kubernetes, Docker, Terraform, CI/CD

Pipelines, GitHub/GitLab, GitOps, GitHub Actions, Jira, Jenkins, CircleCI, Datadog,

Slack.

 Graduate degree in a quantitative discipline (Computer Science, Engineering,

Statistics, Operations Research, etc.) or equivalent practical experience

 Experience communicating and/or teaching technical concepts to non-technical and

technical audiences alike

 5+ years of engineering and technical deployment experience in a customer-facing

set up

 Should scoped and delivered complex systems in rapid and ambiguous

environments

 Delivered production-grade code across frontend and backend using Python,

JavaScript, or similar stacks

 Understand how AI model behaviour affects product experience

 Communicate clearly with engineers, product teams, and customer stakeholders

 Flag risks early and seek attention as per the severity

Key responsibilities:

 Help clients integrate and adopt the offerings; demonstrate the impact / outcomes the

offerings commited such as KPI improvements and help client succeed

 Embed within the client landscape, understand their domain and co-develop

solutions with the core product engineering teams

 Own technical delivery across multiple deployments from prototype to stable release

 Build bespoke AI and transformative agentic AI solutions

 Technical debugging and root cause analysis

 Rapid prototyping

 Implement and administer best practices