Prasanna Kumar

• Own product features end to end — from talking to users and shaping the roadmap to writing full-stack code, shipping to production, and supporting customers directly.
• Translate customer pain points and business requirements into working software, making independent design and UX decisions to build experiences that solve real problems.
• Build and ship production Python services and REST APIs, embedding Generative AI / LLM capabilities into the product to automate workflows and unlock new features.
• Prioritize against the product roadmap, estimate technical effort, write clear technical specs, and keep quality high through code review and automated testing in CI/CD.
• Measure success by customer impact over lines of code — iterating fast on user feedback and rebuilding when the data points to a better solution.

Stack—Python · REST APIs · Generative AI · Product · CI/CD · Azure

• Built an HR AI virtual assistant on the Rasa stack — job discovery, FAQs, candidate pre-screening, interview scheduling, and personalized job recommendations.
• Developed and optimized RESTful APIs (GET / PATCH / DELETE) for client-specific bot configuration, cutting manual intervention by implementation teams by 40%.
• Designed an API automation framework with Karate covering every bot-team service, reducing manual QA effort by 50% and accelerating the deployment lifecycle.
• Integrated multi-channel experiences — Web, SMS, MS Teams, WhatsApp, Facebook — with event-driven architectures for seamless data flow across systems.
• Enforced code quality via PyTest, Pylint, and SonarLint on Git/GitHub with Jenkins CI/CD; led OOP-based internal-gig business logic and its integrity constraints.

Stack—Python · Sanic · Rasa · REST · MongoDB · SQL · Jenkins · Karate

• Contributed to the end-to-end SDLC of high-availability banking production systems, holding to strict security and performance standards.
• Developed robust REST APIs for seamless data exchange with third-party banking modules.
• Built automated background schedulers for high-volume batch processing and system monitoring.
• Optimized complex queries and relational data models for integrity and responsiveness under heavy load.

Stack—Java · Spring Boot · MongoDB · Postman · SQL