Experienced AI Software Engineer with a Master’s in IT (AI specialisation) and 3 years of IT experience. Versatile in ML, SQL, DevOps, software development, and QA, adept at integrating diverse skills to drive impactful solutions. Adaptable and a quick learner, excelling in rapidly evolving IT environments.
– Managed and oversaw 120 releases per year for organisation, including special releases.
– Revamped commit process for seamless integration, shifting from a limited 4-hour commit window to a 4-hour pause only during deployment, thus improving efficiency and
flexibility.
– Triaged over 200+ production issues and produced RCA’s resulting in improved defect leakage metric.
– Managed over 100 staging deployments and 50 production deployments, ensuring streamlined processes and prompt issue resolution.
– Implemented CI/CD workflows and Automated Deployment System for organisation, reducing deployment duration from 4 days to 12-14 hours, saving $75,000 annually.
– Served as the 24/7 primary on-call for staging environment issues for a duration of 3 years and contributed to the production on-call team on a round-robin basis for 2.5 years.
– Trained and mentored over 25 candidates (spanning graduate to senior software engineers) in processes and procedures.
– Enhanced SupremeOne (internal deployment automation tool) with multiple value-added features such as the release tracking chart and a custom script execution portal, providing
secure access to various applications like Slack, Google Calendar and Sheets, among others.
– Designed webpages with a focus on usability and user-centric design.
– Defined, validated and communicated product vision, objectives, and roadmap to the product team and the client.
– Translated customer insights into well-defined user stories for the product team.
– Contributed to sprint planning and review, ensuring timely, budget-conscious feature delivery.
– Implemented agile methodologies, reducing project delivery time by 25%.
– Developed cross-platform mobile and web applications for patient and clinic management.
– Implemented rigorous testing and automated CI/CD workflows using GitHub actions and AWS Elastic Beanstalk for enhanced efficiency.
– Designed an evidence retrieval system to retrieve evidences most related to the claims.
– Evaluated the results to assess performance, effectiveness and accuracy.
– Developed a classification model using transformers to categorize claims and evidence.
– Model was ranked 4 out of 81 participants in a university-hosted competition.