Forward Deployed Engineer - Artificial Intelligence/Machine Learning (India)

Forward Deployed Engineer - Artificial Intelligence/Machine Learning (India)

28 Sep
|
People Creation
|
India

28 Sep

People Creation

India

Forward Deployed Engineer (FDE)

A client-facing engineering role delivering AI-driven solutions directly with clients. This is not a backend seat.

Key Responsibilities:

- Client-facing ownership: Presents to clients, runs discovery conversations, translates business problems into technical solutions, and owns delivery end to end.
- Production LLM systems: Has designed and shipped LLM-powered systems in production. ML theory or POC-only experience is not enough.
- RAG and agentic workflows: Architects RAG pipelines end to end and builds agentic workflows with tool use and multi-step orchestration.
- Evals and model decisions: Writes and runs evals to measure quality. Makes deliberate choices on model selection, routing, context management, and cost/latency tradeoffs.
- LLM failure modes: Understands hallucination, prompt injection, and degraded retrieval, and engineers around them.
- Independent full-stack delivery: Ships a working product alone. Goes from a whiteboard conversation to a working POC in days, then hardens it for production.

Tech Stack:

- Backend: Strong in one or more of Java, Golang, Python, Node.js, or .NET. Designs clean REST APIs,



models data sensibly, handles auth, and reasons about performance and error handling in production.
- Frontend: Builds functional, presentable UIs in React, Angular, Vue.js, or similar.
- Databases: Fluent in SQL (Postgres or MySQL) and at least one NoSQL store. Vector DB experience (pgvector, Pinecone, Qdrant) is a robust plus.
- Knowledge bases: Experience building retrieval knowledge bases (chunking, embedding, indexing) and knowledge graphs (Neo4j, graph-based RAG).
- Cloud and containers: Hands-on deployment on at least one of AWS, Azure, or GCP. Docker is a must; Kubernetes is a plus.
- CI/CD and observability: Sets up pipelines, manages environments and secrets, and maintains logging and monitoring without a dedicated DevOps engineer.
- Security: Applies sensible defaults for auth, API keys, data handling, and client data isolation. Implements prompt injection defenses and guardrails.
- Ambiguity tolerance: Thrives with loosely defined problems, shifting requirements, and minimal hand-holding.

📌 Forward Deployed Engineer - Artificial Intelligence/Machine Learning (India)
🏢 People Creation
📍 India

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