Product Engineering
Development
D&A, MLOps
DevOps
Automation Testing
Mentoring, T&D
Results-driven Software Engineer | DevOps Engineer | QA Engineer | Test Automation Engineer | AI/ML Engineer with 10+ years of experience delivering enterprise software solutions across Software Engineering, Quality Engineering, DevOps, Cloud, Automation, and AI-powered platforms. Experienced across the Software Development Life Cycle (SDLC), Software Testing Life Cycle (STLC), DevOps, DevSecOps, Model Development Life Cycle (MDLC), MLOps, AIOps, Agile, and CI/CD, driving quality, automation, security, and operational excellence throughout the software lifecycle. Strong expertise in software development, application modernization, test automation, API and web automation, automation framework development, CI/CD pipelines, cloud engineering, release management, production support, incident response, root cause analysis, observability, SRE, SLOs, SLIs, and disaster recovery. Experienced in AI/ML Quality Engineering, including AI model validation, ML pipeline testing, model evaluation, feature validation, data quality testing, regression testing, model drift detection, continuous monitoring, and quality assurance throughout the MDLC and MLOps lifecycle. Passionate about applying Artificial Intelligence (AI), Generative AI, Large Language Models (LLMs), Agentic AI, Prompt Engineering, Retrieval-Augmented Generation (RAG), AI-assisted Software Engineering, AI-driven Test Automation, AI Observability, AI Governance, Intelligent Quality Engineering, Predictive Analytics, and Responsible AI to improve software quality and engineering productivity. Core Skills: • Software Engineering • DevOps & DevSecOps • QA & Quality Engineering • Test Automation Engineering • SDLC, STLC, MDLC • MLOps & AIOps • AI/ML Testing & Model Validation • CI/CD & Release Automation • AWS Cloud • REST APIs & Microservices • SRE, SLOs & SLIs • Incident & Problem Management • Performance, Integration & Regression Testing • Agile & Scrum I enjoy collaborating with software engineers, DevOps engineers, QA teams, ML engineers, data scientists, architects, product owners, and business stakeholders to build secure, scalable, resilient, and AI-enabled solutions that deliver measurable business value through engineering excellence and continuous innovation.
Software product engineering (SPE) is designing, developing, testing, deploying, and maintaining software products. SPE includes creating and maintaining a product from its conception to the end of its life. Software product engineering has several benefits – improved quality, reduced costs, increased efficiency, and faster time to market.
Web development refers to the creating, building, and maintaining of websites. It includes aspects such as web design, web publishing, web programming, and database management. It is the creation of an application that works over the internet i.e. websites.
"Data Analytics" refers to the process of extracting meaningful insights from data using statistical methods and visualization techniques, while "MLOps"(Machine Learning Operations) is a set of practices that automate and streamline the entire lifecycle of a machine learning model, from development to deployment and monitoring, ensuring its effectiveness in a production environment; essentially, data analytics focuses on extracting insights from data while MLOps focuses on operationalizing machine learning models to continuously deliver value in real-world applications.
Application support and DevOps engineering are related fields that involve managing the development, testing, and support of software. DevOps is a methodology that aims to improve collaboration and communication between development and operations teams.
Test automation is the practice of automatically reviewing and validating a software product, such as a web application, to make sure it meets predefined quality standards for code style, functionality (business logic), and user experience.
"Mentoring, Training & Development" is a type of training in which a more experienced individual (mentor) provides guidance and support to a less experienced person (mentee) alongside structured training programs designed to enhance their skills and knowledge, ultimately leading to career advancement and improved performance.