Posted 11 July, 2026
Forward Deployed Engineer
Diverse Lynx
Bengaluru,Karnataka
Full Time
Reference: 365_569689_26-01351
Role Summary
Embeds with client teams, understands manual business workflows, and builds AI-agent-powered automation to
replace them. Owns the solution end-to-end — discovery, build, deploy, iterate — working directly with clients with
minimal direction.
Agentic AI
• LLM API fundamentals — LLM API integration — tool use, function calling, streaming, context management
• Skill building — Design and publish reusable skills consumable by LLM-powered agent workflows
• MCP (Model Context Protocol) — Build and consume MCP servers; expose and integrate tools for agent use
• A2A communication — Multi-agent coordination, task delegation, result aggregation across agent networks
• RAG pipelines — Vector databases, chunking, embeddings, retrieval pipelines
• Prompt engineering — System prompts, chain-of-thought, evaluation and iteration
• Agent frameworks — Strands as primary framework; awareness of LangGraph, CrewAI, or AutoGen
• Guardrails — Hallucination mitigation, human-in-the-loop checkpoints, agent observability
Backend
• Python 3.10+, async/await, type hints
• FastAPI or equivalent Python web framework
• Basic SQL — query, filter, join; awareness of vector DBs (pgvector, Pinecone, OpenSearch)
• REST API design, JWT / OAuth2
Workflow Automation
Embeds with client teams, understands manual business workflows, and builds AI-agent-powered automation to
replace them. Owns the solution end-to-end — discovery, build, deploy, iterate — working directly with clients with
minimal direction.
Agentic AI
• LLM API fundamentals — LLM API integration — tool use, function calling, streaming, context management
• Skill building — Design and publish reusable skills consumable by LLM-powered agent workflows
• MCP (Model Context Protocol) — Build and consume MCP servers; expose and integrate tools for agent use
• A2A communication — Multi-agent coordination, task delegation, result aggregation across agent networks
• RAG pipelines — Vector databases, chunking, embeddings, retrieval pipelines
• Prompt engineering — System prompts, chain-of-thought, evaluation and iteration
• Agent frameworks — Strands as primary framework; awareness of LangGraph, CrewAI, or AutoGen
• Guardrails — Hallucination mitigation, human-in-the-loop checkpoints, agent observability
Backend
• Python 3.10+, async/await, type hints
• FastAPI or equivalent Python web framework
• Basic SQL — query, filter, join; awareness of vector DBs (pgvector, Pinecone, OpenSearch)
• REST API design, JWT / OAuth2
Workflow Automation
