Alby Rajesh

AI/ML Engineer  ·  LLM Systems  ·  Knowledge Graphs  ·  Retrieval

Turning unstructured data into queryable knowledge
_{Agentic Text-to-SQL  •  Text-to-Cypher  •  Graph RAG  •  Schema-constrained LLM pipelines}

About

I'm an AI/ML Engineer at Feathersoft Info Solutions, building production GenAI systems for enterprise clients in agriculture and healthcare. My work sits where language models meet structured data: agents that write SQL and Cypher, pipelines that extract knowledge graphs from documents, and retrieval systems that ground every answer in its source.

Focus LLM agents and tool calling Knowledge graphs and Graph RAG Hybrid retrieval (BM25 + dense) Structured, schema-constrained extraction

Principles Every answer traceable to a source Schemas over prompt hacks Small, tested, observable pipelines Ship it, measure it, improve it

Featured projects

text2cypher-agent Agentic Text-to-Cypher over Neo4j. A QLoRA fine-tuned Qwen2.5-Coder model writes Cypher; a LangGraph agent validates it with EXPLAIN, self-corrects on errors and answers from the results. Redis cache and memory, LangSmith tracing and execution-accuracy evals.	voice-text2sql A voice data analyst for Postgres. Ask out loud, hear the answer, see the SQL, table and chart. LangGraph agent with DSPy SQL generation tuned by MIPROv2 on an execution-accuracy metric; sqlglot AST guard plus read-only transactions.
unstructured-2-kg PDF → ontology-linked Neo4j knowledge graph. Schema-constrained extraction on vLLM, grounded facts, tiered entity resolution and NCBI Taxonomy / ChEBI / LOINC linking. Dockerised, tested in CI.	repo-copilot An agent for GitHub repositories. Searches code, reads files and commit history, answers with path:line citations, and drafts issues for human approval. Live demo →
multi-agent-research Cited research reports from a document collection. LlamaIndex hybrid RAG on pgvector (vector + full-text, RRF) feeding CrewAI crews in three patterns: sequential, manager-led hierarchical, and a self-reviewing reflection Flow. Retrieval and LLM-judge evals.	hybrid-rag Document Q&A with keyword and vector search fused by Reciprocal Rank Fusion, cited answers, and a UI that explains why each passage was retrieved.

Experience

AI/ML Engineer · Feathersoft Info Solutions  ·  Jul 2025 – present

• Agentic Text-to-SQL assistant and voice agent for an agriculture enterprise, letting business users query operational data in plain language, by chat or by voice.
• Patient knowledge graph for a rheumatology platform, with Text-to-Cypher and Graph RAG over clinical data in Neo4j.
• Autonomous PDF-to-knowledge-graph agent that extracts entities and relationships from documents and loads them into a graph database.

Tech stack

Credentials

• Claude Certified Developer – Foundations · Anthropic · Sep 2026 · score 910 / 1000
• B.Tech, Electronics and Communication Engineering · Rajagiri School of Engineering, Kochi · 2021 – 2025

Open to AI/ML, GenAI and backend engineering roles, in India or abroad.
albyrajeshwork@gmail.com  ·  LinkedIn