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I am an AI/ML engineer and data scientist with a focus on designing, developing, and deploying enterprise-grade ML, LLM, and graph-based retrieval systems. I specialize in building scalable data-driven solutions across banking, healthcare, and financial domains, with strong proficiency in Python and SQL, real-time streaming, and production-grade model deployment. I thrive in Agile environments, collaborating across cybersecurity, fraud analytics, cloud engineering, and architecture teams to deliver reliable, governance-aware AI systems. I am passionate about responsible AI, model explainability, and measurable business uplift from AI-driven workflows.…I am an AI/ML engineer and data scientist with a focus on designing, developing, and deploying enterprise-grade ML, LLM, and graph-based retrieval systems. I specialize in building scalable data-driven solutions across banking, healthcare, and financial domains, with strong proficiency in Python and SQL, real-time streaming, and production-grade model deployment. I thrive in Agile environments, collaborating across cybersecurity, fraud analytics, cloud engineering, and architecture teams to deliver reliable, governance-aware AI systems. I am passionate about responsible AI, model explainability, and measurable business uplift from AI-driven workflows.

Pravalika Kasojjala

Full Stack Developer, Programmer, Developer, +7

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I am an AI/ML engineer and data scientist with a focus on designing, developing, and deploying enterprise-grade ML, LLM, and graph-based retrieval systems. I specialize in building scalable data-driven solutions across banking, healthcare, and financial domains, with strong proficiency in Python and SQL, real-time streaming, and production-grade model deployment. I thrive in Agile environments, collaborating across cybersecurity, fraud analytics, cloud engineering, and architecture teams to deliver reliable, governance-aware AI systems. I am passionate about responsible AI, model explainability, and measurable business uplift from AI-driven workflows.…I am an AI/ML engineer and data scientist with a focus on designing, developing, and deploying enterprise-grade ML, LLM, and graph-based retrieval systems. I specialize in building scalable data-driven solutions across banking, healthcare, and financial domains, with strong proficiency in Python and SQL, real-time streaming, and production-grade model deployment. I thrive in Agile environments, collaborating across cybersecurity, fraud analytics, cloud engineering, and architecture teams to deliver reliable, governance-aware AI systems. I am passionate about responsible AI, model explainability, and measurable business uplift from AI-driven workflows.

Available to hire

I am an AI/ML engineer and data scientist with a focus on designing, developing, and deploying enterprise-grade ML, LLM, and graph-based retrieval systems. I specialize in building scalable data-driven solutions across banking, healthcare, and financial domains, with strong proficiency in Python and SQL, real-time streaming, and production-grade model deployment.

I thrive in Agile environments, collaborating across cybersecurity, fraud analytics, cloud engineering, and architecture teams to deliver reliable, governance-aware AI systems. I am passionate about responsible AI, model explainability, and measurable business uplift from AI-driven workflows.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Language

English

Fluent

Work Experience

Jr. Full Stack Developer at Sayam Organization

February 1, 2025 - Present

Architected and delivered scalable, low-latency platforms using Java 11, Spring Boot, Hibernate, Spring Cloud, Node.js, React, and AWS/Azure Cloud. Modernized legacy monoliths into microservices with Docker, AWS Fargate, and Kafka, cutting infrastructure costs by 62% and improving time-to-market by 30%. Designed and optimized Elasticsearch clusters, achieving 40% faster query responses. Implemented event-driven and reactive architectures sustaining 100K+ msg/sec throughput. Built and optimized CI/CD pipelines accelerating deployment cycles by 70%. Developed and maintained full-stack applications using React, Angular, and Node.js. Mentored junior engineers on Elasticsearch, cloud technologies, and TDD, resulting in 85%+ test coverage and higher team productivity.

Technical Support Specialist at Sandburg

December 1, 2024 - August 22, 2025

Provided technical support and product expertise, ensuring issue resolution and high customer satisfaction. Applied SQL and backend knowledge to troubleshoot and resolve technical problems. Supported backend services development using Java and Python. Assisted with AWS cloud deployments, improving reliability and scalability. Leveraged understanding of distributed systems to support seamless application performance. Escalated complex cases ensuring timely resolution. Collaborated cross-functionally demonstrating strong communication and teamwork. Adapted to new tools and technologies for continuous support improvement.

Programmer at Cognizant

July 1, 2023 - August 22, 2025

Wrote, tested, and debugged Java and Python applications, ensuring high code quality and performance. Conducted software testing and bug fixing to deliver smooth user experiences. Collaborated in an Agile Scrum environment with designers and project managers to meet client requirements. Ensured code quality and adherence to best practices, improving software reliability. Maintained active client communication and participated in sprint planning. Independently learned and adopted new tools and technologies, enhancing development efficiency.

AI/ML Engineer at Johnson & Johnson

March 1, 2024 - Present

Designed and deployed scalable ML/DL models to optimize product development, clinical data insights, and operational efficiency across Johnson & Johnson's digital health initiatives. Built end-to-end MLOps pipelines on AWS using SageMaker, EC2, Lambda, and Step Functions to automate data workflows and enable real-time model inference. Developed and fine-tuned LLMs for document summarization and intelligent data extraction using Hugging Face, LangChain, and OpenAI APIs. Implemented analytics, anomaly detection, and explainable AI (XAI) methodologies, and created AI dashboards with Power BI and Streamlit. Mentored engineers, standardized ML lifecycle practices, and implemented CI/CD pipelines for robust deployment.

ML Engineer / Programmer Analyst at Cognizant

July 1, 2023 - October 24, 2025

Designed and delivered a secure, cloud-based healthcare analytics platform processing 10M+ medical records, integrating Python ML models with a Java Spring Boot microservices backend and React.js frontend to deliver real-time insights for internal analytics teams. Built NLP pipelines using TensorFlow, Keras, and scikit-learn for clinical note classification, patient sentiment analysis, and discharge summary generation. Applied data science methodologies to optimize predictive models and enable scalable data processing, while ensuring regulatory compliance and cross-functional collaboration. Automated CI/CD pipelines and cloud deployments to streamline ML workflows.

AWS Cloud Engineer at Pruthvi Information Solutions Limited

November 1, 2021 - October 24, 2025

Deployed containerized microservices on Amazon EKS, built real-time data processing pipelines using AWS Glue Streaming and Kinesis, and developed ML/DL models using Java frameworks. Engineered end-to-end data pipelines for structured and unstructured data, integrated SAP with AWS CI/CD, and applied DevSecOps practices with Ansible and Terraform. Built secure RESTful APIs and IaC for multi-environment deployments, enabling scalable analytics across hybrid cloud environments.

AI/ML Engineer at Bank of America

March 1, 2024 - Present

Designed and deployed enterprise-scale AI/ML solutions for fraud detection, transaction monitoring, call-center automation, and regulatory compliance across high-volume banking workflows. Developed NLP, computer vision, and time-series models using Python, scikit-learn, Keras, and Hugging Face Transformers, delivering production-grade AI services for real-time call summarization and agent assistance. Fine-tuned LLMs (LLaMA, GPT, BERT, RoBERTa, T5) for summarization and sentiment analysis, improving accuracy and reducing latency through optimization and quantization. Built GraphRAG pipelines combining vector similarity with graph traversal to retrieve interconnected policies, compliance rules, fraud cases, and interaction histories. Implemented secure, low-latency inference via FastAPI and gRPC, deployed on Azure Machine Learning + AKS, with auto-scaling. Enabled drift monitoring, explainability, and governance with SHAP/LIME and CloudWatch.

ML Engineer / Programmer Analyst at Cognizant

December 1, 2021 - July 1, 2023

Designed and developed enterprise AI/ML platforms processing 10M+ healthcare and financial records, integrating Python ML models with Java Spring Boot microservices and React dashboards for real-time insights. Built advanced NLP pipelines using Transformer models (BERT, RoBERTa, DistilBERT, T5), improving classification, sentiment analysis, and summarization accuracy. Implemented GraphRAG solutions to connect clinical entities, patient histories, medical concepts, and claims data for context-aware analytics. Maintained RAG pipelines with FAISS, Milvus, and ChromaDB to improve contextual relevance. Built YAML-driven MLOps pipelines (TFX, Kubeflow, GitHub Actions) to orchestrate data validation, model training, CI/CD, packaging, and deployment across AWS and on-prem environments. Ensured HIPAA/regulatory compliance with RBAC/IAM, encryption, and audit trails; collaborated with cross-functional teams to deliver scalable AI solutions.

AWS Cloud Engineer at Pruthvi Information Solutions Limited

October 1, 2020 - November 1, 2021

Developed and deployed AI/ML models on AWS using SageMaker, Lambda, and containerized inference services, enabling scalable real-time predictions. Built end-to-end data ingestion and transformation pipelines with AWS Glue, Kinesis, Kafka, and Spark. Supported early GraphRAG-style architectures for semantic search and enterprise AI workloads on AWS. Containerized deep learning workloads with Docker and deployed on Amazon EKS to improve GPU/CPU utilization. Implemented DevSecOps with CI/CD pipelines and secure IAM practices; integrated SAP/on-prem systems with AWS AI services for hybrid cloud processing.