Anush Deokar

Full Stack + AI Engineer

I design and ship agentic systems, from the data layer to the product.

I'm a founding AI engineer at Meridian, where I build the core AI platform end to end: RAG pipelines and MCP servers underneath, multi-agent flows in the middle, and the chat and voice agents people actually talk to on top. Before that I spent years as a frontend and full-stack engineer, so I own the whole path, from raw data to the interface.

Outside work I run experiments and build side projects: taking ideas apart, testing them carefully, and writing up what I learn.

Work

  1. Jun 2025 — Present

    Founding AI Engineer · Meridian

    Founding engineer on the AI platform behind Meridian's products, designing systems end to end, from ingestion and retrieval to multi-agent flows in production.

    • Architected the RAG pipelines at the centre of Hermes, Meridian's core AI platform: ingestion, retrieval and grounding that every product agent builds on.
    • Built the Atlas MCP server, a standalone multi-tenant MCP server that exposes lead and lead-journey data to any MCP-compatible agent, with JWT and service-account auth, tenant resolution shared with hermes-core, and role-aware actions.
    • Designed and shipped multi-agent flows on Hermes: production chat agents that hold real conversations with customers, plus core contributions to the voice agent.
    • Built agents that make decisions, not just replies: judging candidates in AI interviews and qualifying leads in conversation, with results delivered to partner systems in real time.

    Python · TypeScript · LangGraph · MCP · RAG · Node.js

  2. Mar 2024 — Present

    Software Engineer · Trek Health

    • Led core development on turning terabytes of complex healthcare data into accessible, actionable insights for clients.
    • Built a responsive, pixel-perfect product UI on top of systems designed for large-scale data operations, through the product's growth from 0 to $2M+ ARR.

    TypeScript · Next.js · Node.js · Snowflake · AWS

  3. Jul 2023 — Apr 2024

    Software Engineer · matrice.ai

    • Led and maintained the main product's React + TypeScript frontend, and backend microservices for image annotation.
    • Integrated ML models into the product and coordinated testing with the ML team.

    React · TypeScript · Go · Node.js · AWS

  4. 2023

    B.Tech, Computer Science and Engineering · IIT Jodhpur

Projects

Current project

Tiny Frontier

Cheap memory in small LLMs

How do modern LLMs keep memory cheap? I'm rebuilding sliding-window attention and attention sinks from scratch, testing them with controlled multi-seed experiments, all on a $0 compute budget.

1.8e-4
max logit difference loading Google's Gemma 3 270M into my own code, with identical greedy decoding
5.8×
less KV cache at 4K tokens for a 5:1 local:global model that matches a hybrid beating full attention
32 / 32
buckets where evicting an attention sink hurt, after one change to the training data switched the sink on
Read the seriesCode PyTorch · From scratch · Multi-seed experiments

Earlier

Writing

Tiny Frontier · Rebuilding the memory tricks of modern LLMs at tiny scale, one controlled experiment at a time.

All writing