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Hi, I’mJay Kanara.

I build backends, data pipelines and AI agents, plus the web and mobile apps on top. Then I make them faster and cheaper to run.

Now
Independent engineer since August 2025
Before
Full-stack engineer at SR Analytics and iTinker
Based in
India, where it’s right now
Clients since going independent
20+
Countries they’re based in
5+
Cloud cost I cut, per month. Capacity now follows demand, and scheduled jobs replaced servers that ran around the clock. See how
From $5,000to $72/ month
98.56% saved

The line so far.

Scroll to ride it, from today back to day one.

Prefer one page? Download my resume PDF, 34 KB

  1. Independent

    Freelance engineer and consultant

    Since Remote, clients in 5+ countries

    I work directly with founders and engineering teams. Most of it is backend work: AI agents, machine learning features, Go services and the pipelines that feed them. When a project needs the web or mobile app on top, I build that too, and I make all of it cheaper to run.

    Agentic AI
    LLM agents that take real actions, from calling APIs to querying databases, and hand off to a person when they should. Tested before launch, traced after.
    Machine learning
    Forecasting, classification and ranking models, shipped as versioned, monitored endpoints with pipelines that keep them fed.
    Go backends
    APIs generated from an OpenAPI contract, with role-based access, PostgreSQL underneath, and deploys on Docker and AWS that nobody has to babysit.
    Cost & performance
    I find the slow path and the idle spend, then design both out. Usually with automation. Rarely with more hardware.

    StackGo, Python, TypeScript, LangGraph, Claude & OpenAI APIs, MCP, pgvector, PyTorch, scikit-learn, PostgreSQL, Docker, AWS

  2. SR Analytics

    Full-stack engineer

    to Pune, India

    A B2B analytics platform used by many client organizations. I worked on embedded Power BI reports, ETL from 15+ third-party APIs, multi-tenant access control and the cloud underneath. Reports got faster, and the cloud bill got a lot smaller.

    Embedded report load
    From 17sto 2s
    Less spent on infrastructure
    98.56%
    Faster reporting
    5×

    StackJava, Kotlin, Node.js, Python, Next.js, PostgreSQL, Redis, Jenkins, Power BI, AWS, Azure, Vercel

    Read the case study : SR Analytics

  3. iTinker

    Full-stack engineer

    to Chandigarh, India

    Second-hand listings are scattered across marketplaces that don’t talk to each other. I helped pull them into one live, searchable catalog with Kotlin microservices, a scraping engine, Elasticsearch and updates pushed straight to the browser.

    Faster scraping and API responses
    4×
    Updates over Kafka, SSE and WebSockets
    Live

    StackKotlin, Spring Boot, Next.js, PostgreSQL, Elasticsearch, Kafka, Redis, Selenium, Jsoup, AWS

    Read the case study : iTinker

  4. Where it started

    B.Tech in Computer Engineering

    to Charotar University of Science and Technology

    Four years of computer engineering. I graduated with a CGPA of 8.92 out of 10.

Where I’m most useful.

Backend is where I go deepest. Most projects start with one of these four, and plenty end up touching all of them.

  • AI agents & LLM features

    Assistants and agents that do real work inside your product. They call your tools, read your data, stay inside guardrails, and ship with tests you can rerun every time the model changes.

    Tools: Python, LangGraph, Claude & OpenAI APIs, MCP, pgvector

  • Machine learning in production

    Models that make it out of the notebook and into your product. Feature pipelines, training jobs, versioned endpoints, and monitoring that warns you when the data starts to drift.

    Tools: Python, PyTorch, scikit-learn, pandas, FastAPI

  • Backends that hold up

    APIs with clear contracts, permissions that still hold at customer number fifty, and real-time features only where they earn their keep.

    Tools: Go, Kotlin, Java, Node.js, PostgreSQL, Redis, Kafka

  • Cost & performance rescue

    For products that work but feel slow or cost too much. I measure first, then cut. One report went from 17 seconds to 2. One cloud bill fell by 98.56%.

    Tools: AWS, Azure, Docker, Kubernetes, Jenkins, Power BI

  • The app on top, web or mobile

    When the backend needs a face, I build that as well: a web app your team works in every day, or a phone app your customers carry around. Same repository, same weekly demo, nobody new to brief.

    Tools: Next.js, React, TypeScript, Flutter, Kotlin for Android, Swift for iOS

How a project runs.

Four stops, in the same order every time.

  1. Step 1: Call

    Thirty minutes on what you’re building and what’s in the way.

  2. Step 2: Plan

    Scope, architecture, milestones and cost, in writing, before any code.

  3. Step 3: Build

    Working software in your repository from week one, with a demo every week.

  4. Step 4: Handover

    Docs, tests and runbooks. Nothing is left depending on me.

Toolbox.

What I reach for, grouped the way I use it.

Languages
Go, Python, Kotlin, Java, TypeScript, Swift, Dart, SQL
AI & ML
LLM agents, RAG, LangGraph, MCP, Claude & OpenAI APIs, pgvector, PyTorch, scikit-learn
Backend
Spring Boot, Node.js, Express, REST, OpenAPI, Microservices, WebSockets, SSE
Data
PostgreSQL, Redis, Elasticsearch, Kafka, ETL, Power BI
Cloud & delivery
AWS, Azure, GCP, Vercel, Docker, Kubernetes, Jenkins, GitHub Actions
Web
Next.js, React, TypeScript, Tailwind CSS
Mobile
Flutter, Android with Kotlin, iOS with Swift

Tell me what you’re building.

A few lines will do. What it does, where it’s stuck, and when you need it. I’ll come back with questions or a plan.

Book a call

30 minutes on video. Pick any open slot.

Rather write?

thejaykanara@gmail.com