Anant Gabhane
a Gen AI full-stack developer and product builder with deep experience across engineering, product strategy, and user-centric design.
a polymath who bridges technical architecture with business outcomes to create impactful, scalable solutions.
Experience
ApexaiQ Technologies
Develop and maintain scalable web application using Vue.js, JavaScript, Node.js, Express, MongoDB, and PostgreSQL.
Design and implement new features based on customer requirements, improving usability and performance.
Debug and resolve production issues, ensuring system reliability and smooth user experience.
Optimize backend and frontend performance to support growing data and user scale.
Built and curated Lucene-based base queries across multiple integrations (AWS, GCP, Azure, CrowdStrike, etc.), enabling accurate asset retrieval via NLQ and Chatbot systems.
Led end-to-end testing of AI-powered Chatbot and NLQ systems, validating NLP-to-Lucene query translation, prompt accuracy, and multi-cloud data integrations.
Designed and maintained comprehensive prompt libraries and test datasets (training prompts, NLQ tests, chatbot tests, extended data queries) for structured validation.
Developed scalable and modular test frameworks, executing regression, chained prompt, and prompt injection testing to ensure system reliability and security.
Classified prompts, bugs, and UI issues using structured tagging (pass/fail, categories), improving traceability, debugging, and reporting efficiency.
Validated extended data queries and AI-generated responses across environments (staging & production), ensuring correctness, performance, and continuous model improvement.
Engineered, build and maintained API integrations for multiple platforms including RiskSense, Microsoft Defender, Tanium, Cycognito, Vectra AI, Automox, Zero Networks, Kubernetes, OpenShift, and more.
Built reusable API wrappers to standardize data ingestion and improve integration efficiency.
Enhanced multiple existing integrations (e.g., Infoblox) to improve performance and reliability.
Mentored and onboarded 4 developers, accelerating team productivity and knowledge transfer.
Delivered $20,000+ in value addition through process optimization and automation.
Eliminated 600+ duplicate records, significantly improving data integrity.
Designed and implemented 23 automation rules for compliance, deduplication, and tagging.
Built 21 tag groups, enabling structured tagging of 2,500+ devices for better asset management.
Identified 640+ non-compliant devices, strengthening security posture and compliance tracking.
Developed pre-processing feed rules to enhance data filtering and ingestion efficiency.
Managed 500+ customer support tickets, ensuring timely resolution and high customer satisfaction.
Participated in customer calls, capturing insights and translating them into actionable engineering requirements.
Managed a team of 4 developers while simultaneously supporting two high-value clients: Lunarspace and Concordium (a privacy-focused Layer-1 blockchain platform) - balancing tight deadlines, client expectations, and resource constraints in a fast-paced environment. Authored comprehensive legal and technical developer handbooks to standardize onboarding, compliance, and best practices for new recruits.
In Between These Experiences
I've been consistently exploring, learning, and documenting my journey into AI systems, one concept at a time. What began as curiosity has evolved into a structured effort to understand how real-world AI systems are designed, built, and deployed.
It started with diving into AI Engineering concepts inspired by Chip Huyen, where I explored how modern AI systems go beyond models — covering topics like data pipelines, evaluation, system design, and production challenges. Through writing, I broke down complex ideas into simpler explanations, strengthening both my understanding and communication.
Next, I worked through the Oracle Cloud Generative AI Course, gaining hands-on exposure to foundational concepts like LLMs, embeddings, vector databases, and enterprise AI use cases. This phase helped me connect theory with practical implementations in real-world cloud environments.
Alongside this, I documented my learning from the Chai & Code Cohort, capturing live insights on AI, backend systems, and engineering fundamentals. These notes reflect my ability to learn in fast-paced environments and translate raw knowledge into structured, usable content.
Through these blogs, I've built a habit of learning in public, continuously refining my understanding of AI systems, prompt engineering, and real-world applications. Each article represents a step forward — from beginner concepts to more practical, system-level thinking.
This journey is less about finished products and more about building strong fundamentals, consistency, and clarity of thought — preparing myself to contribute meaningfully to real AI-driven systems.
Education
2019 - 2023
Achievement
GitLab Contributions
GitHub Contributions
Research Publications
2023 SSGM Journal of Science & Engineering Vol. 1 No. 1 (2023): Proceedings of INSCIRD-2023
Authors: Anant Gabhane
View PublicationAbstract
Machine learning algorithms for improving animal health monitoring have accelerated the creation of ML applications for behavioral and physiological monitoring systems, including ML-based animal health monitoring systems. Currently, farm animals are raised all over the world, and it is necessary to monitor their physiological processes. It is suggested in this article to use machine learning models to continuously monitor each animal's vital signs and look for biological changes. In this model, crucial data is gathered via IoT devices, and data analysis is carried out using machine learning techniques to identify potential dangers from changes in an animal's physiological state. The results of the experiments demonstrate that the suggested model is accurate and efficient enough to identify animal situations. For our purposes, the CNN and YOLO accuracy of more than 90% is a promising outcome.
Tech Stack
I'm a generalist at heart who can build with anything, but here's the core stack I've spent the most time with:
Writings & Blogs
I host my thoughts on Hashnode rather than building a custom site. Instead of overengineering and reinventing the wheel, I prefer leveraging a mature platform that lets me focus on what matters: sharing insights on AI systems, product strategy, and technical architecture.
Library
Dev
Casual Reads
*and many more, these are just one of my best reads
Thing about me
Beyond engineering and build systems, I find balance in the tactile and the thoughtful. Whether it's exploring the nuances of complex architectures or spending time in the real world, my approach to life is driven by curiosity and a desire to understand how things work at their core. I'm a first principle thinker.
I believe that the best products are built by people who have a diverse range of interests. It's the unique combination of technical depth and human perspective that allows us to create technology that actually resonates.
Pomodoro Timer
You've reached the end! Or have you? Before you vanish into the digital void, I've got a quick Pomodoro Timer to help you focus better on your next big thing (or just to remind you to stop doomscrolling).