AI/ML EngineerGenerative AI & Agentic Systems
Kolchelma Sai KiranBuilding intelligent systems with LLMs, agents and retrieval.
1+ years building enterprise Generative AI, agentic and RAG systems for pharmaceutical and business intelligence use cases — agent orchestration, MCP tooling, knowledge graphs, safety guardrails and the evaluation harnesses that prove any of it works.
Hyderabad, Telangana, IndiaML Associate — AI/ML Engineer at Avira Digital Technologies
- 1+ yrs
- Experience
- 10+
- LangGraph agents built
- 85–90%
- Migration accuracy
- 3
- Model providers integrated
Full-time + internship
Orchestrator / sub-agent
Tableau → Power BI
OpenAI, watsonx, Llama
What I work on
From agent orchestration down to the retrieval layer
The work spans the whole stack of an AI system — routing and orchestration at the top, tool protocols and memory in the middle, graph and vector retrieval underneath, and evaluation across all of it.
Generative AI
Agent orchestration, retrieval, and evaluation.
Machine Learning
Model training, fine-tuning, and classical ML.
Data & Retrieval
Graph and vector stores behind the retrieval layers.
Backend & Cloud
Service layers, deployment, and experiment tracking.
Selected work
Featured projects
Enterprise platforms, client retrieval systems and self-directed infrastructure work. Client projects are described at the level of detail that appears on my resume.
Athena — Enterprise Agentic AI Platform
Avira Digital Technologies — internal product
Provider-agnostic LLM gateway, MCP tool servers, layered agent memory, guardrails and an LLM-as-judge evaluation harness.
Clinical Knowledge Graph RAG
Avira Digital Technologies — BMS client
A clinical Q&A retrieval system that moved from hybrid-search RAG to Graph RAG once relationship modeling became the real bottleneck.
Agentic Data Structuring & Query Platform
Avira Digital Technologies — BMS client
An orchestrator/sub-agent pipeline that turns raw multi-source data into tagged, queryable records — and answers questions about it in plain English.
Meta-RAG — Adaptive Model-Routing Gateway
Self-directed project
A self-directed inference gateway that classifies query complexity and routes across retrieval strategies and model tiers — then tunes its own thresholds.
Experience
Where I have worked
Open to freelancing
Available for selected AI/ML projects
Taking on a small number of engagements alongside full-time work — which means I am selective, and honest about timelines before we start.
Custom RAG Systems
Retrieval over your own documents, data or knowledge base - including the cases where naive chunk retrieval falls apart and the domain needs to be modeled as a graph.
AI Agents & Agentic Workflows
Multi-agent systems that do real work against real tools - orchestrator/sub-agent architectures rather than one prompt asked to do everything.
MCP Tool Servers & Integrations
Standardized tool access for your agents, so adding the next integration does not mean inventing another bespoke protocol.
LLM Chatbots & Assistants
Assistants grounded in your content that answer from what you actually published, and say so when they do not know.
Natural Language to SQL / Query
Let non-engineers ask your database questions in plain English, against the live schema rather than a stale snapshot.
Guardrails & AI Safety Review
Input and output screening for systems that touch regulated or personal data - and a look at what your agent does when someone tries to talk it out of its instructions.
Have an AI problem worth solving?
Whether you are hiring, scoping a freelance build, or just want to compare notes on agent architecture — the inbox is open.