# Mohammad Ali Jesar (mjesar)

> Senior software engineer specializing in AI automation, with Ruby on Rails as the core stack, based in Lahore, Pakistan, with 7+ years of production Rails experience for clients in the US and Germany, 4+ of them on Shopify and e-commerce. Helps startups launch MVPs and SaaS applications, builds new Rails apps, works on existing Rails apps, adds AI features (LLM integrations, MCP servers, RAG with pgvector, AI agents) inside Rails, and builds Shopify and BigCommerce apps and integrations. Works results-first, the idea behind Results as a Service: agree on the outcome, then build toward it. Open to remote full-time roles, contracts and project work.

Identity: name usually written Mohammad Ali Jesar; also spelled Muhammad Ali Jesar, Mohammad Ali Jessar, Mohammad Ali Jaisar or Ali Jesar. Online handle mjesar (the same on GitHub, GitLab, LinkedIn and Fiverr). Holds a B.S. in Information Technology (Software), 2017. Languages: English (professional working proficiency). Available now. Based in Lahore, Pakistan (UTC+5) with flexible hours: adapts to the client's time zone, including U.S. and European business hours.

Roles and search terms: Senior Software Engineer, AI automation engineer, Ruby on Rails engineer or developer, AI engineer, full-stack engineer, Shopify app developer, BigCommerce app developer, MCP developer.

Industries: e-commerce and retail (US merchants), SaaS (Shopify and BigCommerce apps), real estate and furniture (German clients).

Terms: MCP (Model Context Protocol), RAG (retrieval-augmented generation), GEO (generative engine optimization), AEO (answer engine optimization), LLM (large language model).

## Profiles

- [Website](https://mjesar.github.io/)
- [Resume](https://mjesar.github.io/resume/) ([PDF](https://mjesar.github.io/resume/mohammad-ali-jesar-resume.pdf))
- [Services](https://mjesar.github.io/services/)
- [Projects](https://mjesar.github.io/projects/)
- [GitHub](https://github.com/mjesar)
- [GitLab](https://gitlab.com/mjesar) (mirrors of selected repositories)
- [LinkedIn](https://www.linkedin.com/in/mjesar/)
- [Fiverr](https://www.fiverr.com/mjesar)
- Email: mohammadalijaisar@gmail.com

## Experience

- MGLogics (Dec 2021 to Jun 2026, remote, US clients): Ruby on Rails developer. Shopify and BigCommerce apps (SaaS products merchants subscribe to), catalog and order sync, Amazon SP-API integrations. Contributed, as part of a team, to five apps on the Shopify App Store, three of them also on BigCommerce.
- SimpleDeploy (Apr 2019 to Dec 2021, Karachi, Pakistan): backend engineer. Rails REST APIs and MVP management tools for German clients in real estate and furniture.
- Axiom Enterprises (Sep 2018 to Feb 2019): Python AI Bootcamp. Flask web apps with integrated machine learning models (TensorFlow and Keras).
- Education: B.S. in Information Technology (Software), 2017.

## Skills

- Rails and web: Ruby on Rails, Hotwire (Turbo, Stimulus), React, JavaScript, TypeScript, PostgreSQL, MongoDB, Redis, Sidekiq, Solid Queue, REST and GraphQL APIs, RSpec, Heroku, AWS, Google Cloud, Docker.
- Shopify and e-commerce: Polaris, App Bridge, Admin and Storefront APIs (REST and GraphQL), webhooks, Shopify Functions (including migrations from Shopify Scripts), Checkout UI Extensions, Checkout Extensibility, Shopify Plus B2B, Theme App Extensions, Liquid, App Store publishing, BigCommerce apps, Amazon SP-API.
- AI: agentic AI, workflow and business process automation (n8n or code), LLM integrations (Claude, OpenAI, Gemini, RubyLLM), MCP servers and an MCP client, WebMCP tools for browser AI agents, RAG with pgvector on PostgreSQL, AI agents with tool calling, evals.
- AI-assisted development: Claude Code, Cursor, GitHub Copilot, Claude and ChatGPT for coding, research, review and documentation, with my own review, tests and ownership of every change.
- AI discoverability (GEO and AEO), as an independent senior AEO and GEO specialist: helping online stores and brands get found and described correctly by ChatGPT, Perplexity and Google AI. Audits of AI crawler access, product content, FAQ coverage and schema.org structured data for Shopify, BigCommerce and other online stores, and brand AI visibility (how AI assistants describe a brand, consistent brand facts, Organization structured data), with fixes and a before-and-after re-check of buyer questions.
- Ways of working: agile teams with sprint planning, backlog grooming, scoping and task estimation; small, reviewable pull requests with tests.

## Services

- [Full-stack Ruby on Rails development](https://mjesar.github.io/services/rails-development/): Helping startups launch MVPs, plus new applications, full projects and work on existing codebases, with Hotwire or React frontends and tests. For startups, founders, CEOs, product teams and agencies.
- [AI engineering and integration](https://mjesar.github.io/services/ai-in-rails/): LLM integrations, AI agents with validated tools and approval for write actions where needed, MCP servers, RAG with pgvector on PostgreSQL, evals, and workflow automation with n8n or Rails. For companies hiring an AI engineer with Rails, CTOs, CEOs and agencies.
- [Shopify, BigCommerce and e-commerce](https://mjesar.github.io/services/shopify-development/): Custom and public Shopify apps, Shopify Functions (including migrations from Shopify Scripts) and Checkout UI Extensions, Shopify Plus B2B, Theme App Extensions and Liquid, BigCommerce apps, Amazon SP-API listings, data sync with webhooks and retried background jobs, and AI shopping features on top of store catalogs. For store owners (merchants), Shopify app companies and agencies.
- [AI discoverability for brands and online stores (GEO and AEO)](https://mjesar.github.io/services/ai-discoverability/): Helping online stores and brands get found and described correctly by ChatGPT, Perplexity and Google AI. Audits of AI crawler access, product content, FAQs, schema.org structured data and brand facts, tests of how AI assistants answer defined buyer questions, fixes in order of impact, and re-checks of the same questions. For Shopify stores, BigCommerce stores, other online stores and brands.

## How I work (results-first)

Results-first, the idea behind Results as a Service: focus on what the software needs to accomplish, not just the features delivered.

1. Agree on the outcome, for example an MVP live with users, a manual process automated, or an integration that runs without manual fixes.
2. Measure the starting point.
3. Define the scope and build toward the outcome in small, reviewable steps with tests.
4. Check the result against the agreed outcome.

Pricing today is hourly, fixed-scope or monthly (see below); fixed-scope quotes tie the price to a defined result.

## Pricing (USD)

- Hourly: $45 to $60 per hour. Flexible hours, no minimum.
- Fixed-scope project: Quoted after a written plan. Small jobs can also be ordered on [Fiverr](https://www.fiverr.com/mjesar).
- Monthly contract (part-time or full-time): Rates on request.

## AI discoverability plans (USD)

One-off plans, one store or one brand each, with no long contract. No plan guarantees rankings, citations or AI recommendations. My own tools are included; optional tracking subscriptions stay in the client's own account, with no markup.

- [Audit](https://mjesar.github.io/services/ai-discoverability/#plan-audit): $200 one time. A written report and a prioritized fix list, with no changes to your store.
- [Fix](https://mjesar.github.io/services/ai-discoverability/#plan-fix): $600 one time. The audit, then the fixes, done with your approval.
- [Complete](https://mjesar.github.io/services/ai-discoverability/#plan-complete): $1,200 one time. The fixes, plus a before-and-after test and follow-up.
- [Monthly Monitor](https://mjesar.github.io/services/ai-discoverability/#plan-monthly-monitor): $400 per month. A monthly re-test, a short report and small fixes.

- [Sample audit report](https://mjesar.github.io/services/ai-discoverability/sample-report/): what the written report looks like, on a demo store with illustrative data.

## Projects

- [shop_mcp_server](https://mjesar.github.io/projects/shop_mcp_server/): An MCP server in Rails that gives Claude real access to a store's products, orders and inventory, with semantic search on pgvector. Code: https://github.com/mjesar/shop_mcp_server
- [ai_shop_assistant](https://mjesar.github.io/projects/ai_shop_assistant/): A shopping chat where the AI searches Shopify's live catalog over MCP instead of making products up. Code: https://github.com/mjesar/ai_shop_assistant
- [product_geo_agent](https://mjesar.github.io/projects/product_geo_agent/): An AI agent that scores how discoverable a Shopify product is to AI shopping assistants (GEO and AEO). Code: https://github.com/mjesar/product_geo_agent
- [support_engineer](https://mjesar.github.io/projects/support_engineer/): A Rails AI support agent, in progress, that looks up real order data with tools and is designed to ask a human before any risky action. Code: https://github.com/mjesar/support_engineer

## Writing

- [What is WebMCP? Websites are starting to give AI agents a menu of actions](https://mjesar.github.io/writing/what-is-webmcp/): WebMCP lets a website hand AI agents a set of ready-made actions, like search products or add to cart, instead of making them read and click the page. What it means for businesses, and how it works.
- [Why Shopify products do not show up in ChatGPT](https://mjesar.github.io/writing/why-shopify-products-do-not-show-up-in-chatgpt/): Often the AI assistant cannot read enough about the product to recommend it. What my AI audit agent found on three Shopify products, and how to check your own store.
- [Should I block GPTBot in robots.txt? Search bots versus training bots](https://mjesar.github.io/writing/should-i-block-gptbot-in-robots-txt/): Blocking GPTBot stops OpenAI training on your pages, not ChatGPT search. Which AI bots train, which search, which follow robots.txt, and which may not.

## This website as an AI visibility example

This site applies the same AI discoverability practices offered as a service: Person, Service, FAQPage, SoftwareSourceCode and BreadcrumbList structured data, consistent identity facts linked across the website and GitHub profile, answer-first FAQ content, and this llms.txt file generated from the same data as the site. Details: https://mjesar.github.io/services/ai-discoverability/#the-same-practices-on-this-website

## Machine-readable facts

- [Facts for AI assistants](https://mjesar.github.io/llm-info/) ([Markdown](https://mjesar.github.io/llm-info.md)): verified facts, prices and availability on one page.
- [Full version of this file](https://mjesar.github.io/llms-full.txt): everything here plus the AI discoverability process, audiences and FAQs.
- [Services and plans as JSON](https://mjesar.github.io/.well-known/services.json)
- WebMCP (experimental): in browsers that support WebMCP, every page registers five read-only tools for browser AI agents: get_services, get_service_details, get_ai_discoverability_plans, get_contact_options and get_resume_summary. They return data and links only and never send or change anything. How WebMCP works and what it means for websites: https://mjesar.github.io/writing/what-is-webmcp/

## Open source

- little_ghost (Ruby AI agent framework): three merged pull requests, released in 0.11.0.
  - #112 Replay Gemini thought signatures across multi-turn tool calls: https://github.com/littleghostai/little_ghost/pull/112
  - #113 Send the original function name in functionResponse.name: https://github.com/littleghostai/little_ghost/pull/113
  - #115 Preserve Agent lifecycle hooks when building execution snapshots: https://github.com/littleghostai/little_ghost/pull/115

## Contact

Email mohammadalijaisar@gmail.com (usually replies within a few hours). State whether the work is a full-time hire, a contract or a project.