About Me
I am a Software Engineer II at Genesys, working on next-generation information retrieval systems and AI-powered knowledge platforms. I graduated with a B.Tech in Computer Science & Engineering from Vellore Institute of Technology in 2022. My work focuses on building scalable, knowledge-driven architectures and developing search systems for enterprise applications.
I am passionate about distributed systems, microservices architecture, and building fault-tolerant applications that scale. At Genesys, I played a pivotal role in developing Knowledge v3—a Retrieval-Augmented Generation (RAG) system that transitioned the platform from keyword-based to knowledge-driven architecture, implementing ElasticSearch optimizations and conducting LLM evaluations for AI product development. Previously at Ericsson, I optimized license management systems and implemented security solutions across distributed node clusters.
Away from the keyboard, I'm captivated by the grand narrative of existence—the Evolution of Humankind, the geometry of Cosmology, the paradoxes of Quantum Mechanics, and the forces of Astro- and Nuclear Physics. Exploring these frontiers sharpens my systems thinking and keeps me humble about what we have yet to discover.
I'm open to exploring opportunities and excited to contribute my skills to innovative products. If you're looking for a motivated individual ready to take on new challenges, let's connect!
Expertise
Programming Languages
- Python
- C/C++
- Java
- JavaScript
- PHP
- SQL
Expertise & Technologies
- Amazon Web Services (AWS)
- Distributed Systems
- Microservices
- Information Retrieval Systems
- Django, Flask, OpenSearch
- Docker, Jenkins, MySQL
- Artificial Intelligence
- Multi-threading
- Systems Design, Platform Development
Competitive Programming
- Top 5% on LeetCode with 900+ problems solved
- Consistent algorithmic problem-solving in contests
Genesys
November 2024 - PresentSoftware Engineer II
- Researched and implemented optimal ElasticSearch DSL queries that increased the search accuracy of the existing system by 45%, significantly improving the quality of initial document retrieval
- Researched, designed, and implemented a novel query preprocessing module that resolved a long-standing noise issue in the search system, resulting in an 85% improvement in precision and accuracy, and significantly reducing false positives in production
- Led a comprehensive evaluation and benchmarking of large language models, optimizing for factual consistency, coherence, and relevance, directly influencing LLM selection and future AI product direction
- Played a pivotal role in replacing a legacy keyword system with Knowledge v3, a scalable RAG architecture now serving the entire customer base, contributions included engineering its core components and conversational interface powered by AWS Bedrock LLMs
- Contributed to architecture decisions by identifying true system bottlenecks and strategically reallocating optimization efforts for maximum impact and scalability
- Technology Stack: Python, Flask, NRQL, DynamoDB, Amazon S3, OpenSearch, Amazon Kinesis, Terraform, CloudFormation, Amazon Lambda, Ansible, Docker, Amazon SQS, Amazon Bedrock
Ericsson
January 2022 - August 2024Software Engineer I
- Optimized the Ericsson Charging (EC) application's license manager system by re-engineering the REST API interface, achieving a 90% [10 to 1] reduction in unnecessary alerts triggered, fostering a more efficient licensing experience and high availability
- Streamlined and automated the Ericsson's License Manager certificate renewal process, reducing operational time by 98% [25 minutes to 5 secs], enabling frictionless communication and peak performance
- Designed and led a project within the EC application, which effectively mitigated security vulnerabilities by implementing encryption and decryption algorithms across both node clusters and customer environments
Engineering Intern
- Spearheaded a revamp of various legacy scripts within RHEL7.9, seamlessly migrating them from Python 2 to 3
- Achieved a 10% increase in system throughput through improved memory management and optimization of core libraries
Vellore Institute of Technology
B.Tech in Computer Science and Engineering
2018 - 2022GPA: 8.50
Sri Chaitanya Junior Kalasala
Higher Secondary Education
2016 - 2018Percentage: 96.2%
Natural Language Processing in TensorFlow
DeepLearning.AI
Comprehensive course covering advanced NLP techniques and implementation using TensorFlow framework for building intelligent language processing systems.
Projects
OneNote
Python, Django REST, MySQL, REST API December 2021Developed a task management application with user accounts and personalized task lists using Django MVT framework, MySQL database, and comprehensive REST API's for seamless task operations.
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Python, Neural Networks, TensorFlow, Keras March 2021Developed an email spam filter using neural networks and Natural Language Processing techniques like text tokenization, sequencing, and padding, executed on Google Colab and Jupyter Notebook with TensorFlow and Keras.
View on GitHub