Gudidevuni Vaishnavi
Open to work5 years experienceAI & Backend Engineer
AI & Backend Engineer with 5+ years of experience in AI-driven backend systems and Generative AI.
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Skills & Technologies
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Work Experience
AI /Backend Engineer
CVS, USA
- Designed scalable Python-based backend systems for healthcare document processing and AI workflows.
- Developed microservices architecture using FastAPI for high-throughput document ingestion pipelines.
- Built event-driven distributed systems using Google Pub/Sub for decoupled service communication.
- Integrated LLM-based pipelines for document summarization and structured data extraction.
- Implemented retrieval-augmented generation pipelines for contextual document intelligence.
- Designed REST APIs and OpenAPI specifications for seamless system integrations.
- Optimized database schemas and queries for high-performance data processing workloads.
- Deployed containerized applications using Docker and Kubernetes on GCP infrastructure.
- Established observability using monitoring and logging frameworks for production reliability.
- Collaborated with cross-functional teams to deliver scalable AI-driven healthcare solutions.
Software Engineer
Wells Fargo, India
- Designed multi-agent AI orchestration systems for financial analytics workflows.
- Built scalable LLM-powered backend services for real-time inference processing.
- Developed distributed systems handling high-volume financial data pipelines.
- Optimized backend APIs for low latency and high reliability performance.
- Implemented asynchronous processing using Celery and Redis caching layers.
- Designed secure APIs with OAuth2, JWT, and role-based access control.
- Built monitoring pipelines to track system performance and model behavior.
- Collaborated with stakeholders to translate business requirements into AI solutions.
- Developed CI/CD pipelines for automated deployment and testing workflows.
- Maintained scalable PostgreSQL data models for analytics and reporting systems.
Projects
Meridian Health Document Intelligence Platform
- Designed scalable Python-based backend systems for healthcare document processing and AI workflows.
- Developed microservices architecture using FastAPI for high-throughput document ingestion pipelines.
- Built event-driven distributed systems using Google Pub/Sub for decoupled service communication.
- Integrated LLM-based pipelines for document summarization and structured data extraction.
- Implemented retrieval-augmented generation pipelines for contextual document intelligence.
- Designed REST APIs and OpenAPI specifications for seamless system integrations.
- Optimized database schemas and queries for high-performance data processing workloads.
- Deployed containerized applications using Docker and Kubernetes on GCP infrastructure.
- Established observability using monitoring and logging frameworks for production reliability.
- Collaborated with cross-functional teams to deliver scalable AI-driven healthcare solutions.
Intelligent Banking AI Platform & Scalable Financial Backend Systems
- Designed multi-agent AI orchestration systems for financial analytics workflows.
- Built scalable LLM-powered backend services for real-time inference processing.
- Developed distributed systems handling high-volume financial data pipelines.
- Optimized backend APIs for low latency and high reliability performance.
- Implemented asynchronous processing using Celery and Redis caching layers.
- Designed secure APIs with OAuth2, JWT, and role-based access control.
- Built monitoring pipelines to track system performance and model behavior.
- Collaborated with stakeholders to translate business requirements into AI solutions.
- Developed CI/CD pipelines for automated deployment and testing workflows.
- Maintained scalable PostgreSQL data models for analytics and reporting systems.
Leaderboard Standings
Leaderboard Position Pending
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Assessment Highlights
Assessments Not Completed
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AI Collaboration Score
AI Collaboration Score Pending
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Role Compatibility Profile
Role Compatibility Analysis Pending
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Achievements
Reduced manual document processing time
Reduced manual document processing time by 45% using LLM automation.
Improved routing accuracy
Improved routing accuracy to 97% enhancing operational efficiency.
Increased deployment frequency
Increased deployment frequency by 50% through CI/CD automation.
Achieved 99.9% system uptime
Achieved 99.9% system uptime with scalable cloud architecture.
Reduced API latency
Reduced API latency by 60% through backend optimization strategies.
Scaled AI systems
Scaled AI systems to support thousands of daily inference requests.
Increased automation coverage
Increased automation coverage by 40% across financial workflows.
Improved model evaluation efficiency
Improved model evaluation efficiency by 30% with monitoring pipelines.
About Details
Professional Bio
AI & Backend Engineer with 5+ years of experience building scalable AI-driven backend systems and Generative AI applications. Expert in designing high-performance microservices, LLM-powered pipelines, and distributed systems that transform unstructured data into actionable insights.
Master’s in Computer and Information Technology
Sacred Heart University ( - Present)
Bachelor’s in Electronics and communication engineering
Vidya Jyothi Institute of Technology ( - Present)