Question 1

What is Sanjay Sinalkar's current role and focus at Airpay Technologies?

Accepted Answer

Sanjay Sinalkar is currently a Project Specialist II at Airpay Technologies Limited in the Mumbai Metropolitan Region, India. In this role, he leads technology platform modernization, upgrades legacy systems for improved performance and scalability, designs customer-support chatbot automation solutions, drives project acceleration through AI-assisted workflows (Vibe Coding), and runs technical training programs to enable teams to smoothly adopt modern stacks.

Question 2

What are Sanjay's core technical specialties and programming languages?

Accepted Answer

Sanjay has over 13 years of professional engineering experience. His technical specialties include high-throughput messaging with Apache Kafka and Apache ZooKeeper; backend service development using Node.js, TypeScript, Golang (GoFiber), and LoopBack.io; cloud infrastructure deployment on Amazon Web Services (AWS); caching and database optimization with MySQL, Redis, and Elasticsearch; containerization via Docker; and payment and commerce integrations.

Question 3

How does Sanjay leverage Generative AI and LLM agents in his engineering work?

Accepted Answer

Sanjay actively integrates Generative AI, prompt engineering, and LLMs (OpenAI, Gemini, Claude) to elevate software delivery. He champions AI-driven software engineering methods, implements specialized AI agents and Model Context Protocol (MCP) integrations, automates customer service pipelines with smart chatbot systems, and teaches team members how to leverage AI tools effectively for rapid iteration.

Question 4

What are Sanjay's notable contributions at MyGlamm and Good Glamm Group?

Accepted Answer

Between 2021 and 2025, Sanjay served as a Software Development Engineer III (SDE III) and Senior Software Engineer at MyGlamm / Good Glamm Group. There, he developed high-performance web applications using TypeScript, LoopBack.io, and Node.js. He also engineered secure, cloud-native architectures on AWS, optimized search capabilities using Elasticsearch, designed robust API strategies, and mentored junior developers in writing scalable code.

Question 5

How is this career portfolio optimized for search engines and AI agents?

Accepted Answer

This portal is fully optimized for both humans and machines. For traditional SEO, it features semantic HTML5 tags, optimized title and description meta-tags, OpenGraph/Twitter cards, and rich JSON-LD schemas (Person, ProfilePage, and FAQPage). For AI search engines (like ChatGPT Search, Gemini, and Perplexity), it features a structured, LLM-readable 'llms.txt' file, a comprehensive 'llms-full.txt' directory compiled in plain Markdown, and a semantic, crawlable conversational Q&A structure.

Sanjay Sinalkar | Project Specialist II & Platform Engineer