GEN AI DEVELOPER

ROHIT KALINDINDI

Generative AI Engineer · Full-Stack Developer

+1-660-***-**** *************@*****.***

Generative AI Engineer and Full-Stack Developer with 6+ years of experience designing and delivering LLM-powered applications, RAG pipelines, and intelligent document-processing systems using Java, LangChain, OpenAI, Hugging Face, and GCP. Proven record of measurable impact across government, banking, and enterprise clients — cut manual document processing by 60% with GCP Document AI, raised OCR extraction accuracy to 94%+ using Vision API and NLP post-processing, and deflected 30–40% of customer support tickets through Dialogflow chatbots. Hands-on research experience in fine-tuning and evaluating large language models, prompt engineering, and building GCP-based inference pipelines for AI-assisted applications. Equally strong across the full stack, from React and Angular front ends to Java Spring Boot microservices, Node.js APIs, and CI/CD automation with Azure DevOps and Kubernetes. Known for translating ambiguous business problems into production-grade, cloud-native AI solutions that hold up at enterprise scale.

CORE COMPETENCIES

Generative AI / ML: LLMs, RAG, Fine-tuning (OpenAI, Hugging Face), Dialogflow ES/CX, TensorFlow, PyTorch, Scikit-learn, SpaCy, NLTK

Cloud & DevOps: GCP (Cloud Functions, App Engine, Firestore, Document AI, Vision API), Azure DevOps, AWS Textract, PCF, CI/CD (Jenkins, Nexus), Kubernetes, SonarQube

Backend / APIs: Python, Java, Node.js, Spring Boot, Microservices, RESTful APIs, Webhooks, Tesseract OCR, Snowflake

Frontend: React.js, Angular, TypeScript, JavaScript, HTML/CSS, Material-UI, Bootstrap, Flask

Data & Databases: SQL, Oracle DB, MongoDB, DataStax Cassandra, Pandas, R, Postman

PROFESSIONAL EXPERIENCE

Programmer Analyst / AI Developer · State of Michigan – MDHHS Lansing, MI Feb 2025 – Till Date

Eliminated manual vital-records backlog: Developed and maintained GCP Document AI pipelines that automated document scanning, indexing, and routing, reducing manual processing time by approximately 60%.

Boosted OCR extraction accuracy to 94%+ by layering Google Vision API with SpaCy and Hugging Face NLP post-processing, replacing a brittle rules-based system that had a 23% error rate.

Accelerated release cadence by 40% by hardening Azure DevOps CI/CD pipelines and introducing automated integration tests for chatbot flows and document-processing APIs.

Reduced API latency by 35% by refactoring Python/Node.js backend services and introducing GCP Cloud Functions for event-driven document routing, eliminating synchronous bottlenecks.

Maintained 99.9% uptime for public-facing MDHHS applications by proactively monitoring GCP App Engine and Firestore performance dashboards and resolving anomalies before escalation.

Research Assistant — Generative AI Engineer · Northwest Missouri State University – Maryville Maryville,MO

Nov 2023 – Dec 2024

Assisted in developing Retrieval-Augmented Generation (RAG) solutions using LangChain and OpenAI models to support automated quiz generation and personalized student feedback.

Supported the fine-tuning and evaluation of large language models (LLMs) using Hugging Face and TensorFlow for AI-assisted educational applications.

Participated in research activities involving prompt engineering, model evaluation, and performance analysis to improve the quality of AI-generated content.

Developed Python scripts for data preprocessing, document parsing, and OCR integration using Tesseract and Google Vision API.

Assisted in building and maintaining GCP-based AI pipelines for model inference and automated document processing.

Performed data collection, validation, and testing to evaluate model accuracy and support research experiments.

Collaborated with faculty members, graduate researchers, and development teams to implement AI solutions and prepare technical documentation.

Assisted in integrating REST APIs and backend services to support AI-driven applications and chatbot workflows.

Participated in research meetings, code reviews, and Agile-based development activities while contributing to project deliverables.

Supported the preparation of research papers, technical presentations, and conference materials related to Generative AI and Natural Language Processing.

Full-Stack Developer · TKE Group India Oct 2021 – Aug 2023

Reduced document-processing cycle time by 50% by building end-to-end OCR automation with Tesseract + AWS Textract, eliminating a 3-person manual review queue for a logistics client.

Improved chatbot deflection rate by 38% by integrating Dialogflow CX with SpaCy NLP entity extraction and fine-tuned Hugging Face intent classifiers for a customer-service platform.

Delivered 12 reusable React component libraries with Material-UI that cut new feature front-end development time from 2 weeks to 3 days across 5 project teams.

Achieved CMMI Level 3 audit compliance on first attempt by instituting Git branching strategies, Azure DevOps CI/CD gates, and SonarQube quality thresholds — zero P1 defects post-release.

Full-Stack Developer · Citi Bank India Dec 2019 – Oct 2021

Migrated 8 legacy Angular 1.x portals to React.js — reducing page load times by 45% and cutting annual front-end maintenance effort by 1,200 developer-hours.

Re-architected monolith into 14 Java Spring Boot microservices on GCP, improving horizontal scalability and enabling independent deployments that cut release risk by 60%.

Secured SAML 2.0 authentication across 3 banking applications handling 500K+ daily active users — passed external PCI-DSS security audits with zero critical findings.

Sped up batch-processing jobs by 3 by migrating Oracle DB queries to DataStax Cassandra with optimized read/write patterns, meeting SLA requirements that the legacy system routinely missed.

Integrated Google Dialogflow chatbot for automated customer-inquiry routing, deflecting 30% of tier-1 support tickets and saving ~$200K/year in operational cost.

Junior Full-Stack Developer · Miracle Software Systems Vizag, India Apr 2019 – Nov 2019

Delivered production MEAN-stack application in 4 months — 3 weeks ahead of schedule — handling 10K+ daily transactions for a client data-management portal.

Integrated Dialogflow chatbot that automated 40% of customer queries at launch, reducing support call volume in the first 30 days and earning client commendation.

Improved API response time by 55% through Node.js/Express.js query optimization and cloud-function refactoring, resolving a critical throughput bottleneck ahead of peak season.

EDUCATION

M.S. Information Systems Aug 2023-Dec 2024

B.Tech In Mechanical Engineering Jun 2015-Apr 2019

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