Prajjwal Mishra
4+ years of industry experience building end-to-end data and AI systems, including real-time pipelines, distributed backends, cloud-native infrastructure, and scalable full-stack applications.
Software Engineer · AI/ML · Cloud
I build production-ready AI systems end-to-end — from multimodal models to cloud-native infrastructure and polished user interfaces.
Trusted by Industry Leaders
Companies I've Worked With
About Me
Software Engineer with 4+ years of experience building production-grade distributed systems, real-time data pipelines, and scalable backend architectures. Currently pursuing an MS in Computer Science (AI/ML) at the University at Buffalo, combining strong industry execution with advanced research exposure.
At UnitedHealth Group, architected event-driven microservices processing 100K+ events/second, built centralized monitoring platforms that reduced debugging time by 70%, and designed Kafka- and Kubernetes-based streaming workflows that lowered data latency by 30%. Delivered HIPAA-compliant systems while improving overall scalability by 35% through robust system design and cloud-native patterns.
I operate at the intersection of backend engineering, cloud infrastructure, and AI-driven innovation, delivering end-to-end solutions—from real-time telemetry platforms supporting 10,000+ vehicles to immersive AI-powered VR healthcare applications—with a strong focus on reliability, performance, and business impact.
MS in Computer Science
University at Buffalo
2024 - 2025
AI/ML specialization with focus on multimodal systems
4+ Years Industry
UnitedHealth · Deloitte · KPMG
2021 - 2024
Backend, Platform, and Data Engineering
Research & Development
University at Buffalo
2024 - Present
VR applications and cognitive therapy systems
Experience
Graduate Research Assistant
Aug 2024 – PresentUniversity at Buffalo
Research & Development
- •Built and maintained backend Python systems following secure coding patterns, accessibility considerations, and engineering best practices.
- •Developed an agentic AI-powered adaptive web extraction system using Playwright, LangChain, and large language models, resilient to dynamic DOM changes, reducing manual effort by 60%.
- •Co-developed AutoRSR, an ML inference pipeline with production-grade logging and telemetry, reducing evaluation time by 60% and increasing clinical screening throughput.
- •Participated in structured code reviews, applied peer feedback, and aligned implementations with team coding standards and design guidelines.
- •Integrated observability signals including logs and metrics to support troubleshooting, availability monitoring, and performance analysis.
Software Engineer
Sep 2021 – Aug 2024UnitedHealth Group
Backend & Data Engineering
- •Architected and engineered cloud-native backend and RESTful microservices in Java, Spring Boot, and Python, contributing to the modernization of 15+ legacy healthcare systems into a scalable microservices platform serving 200K+ members.
- •Led on-premises database to AWS Kafka migration, designing secure ingestion pipelines to stream transactional and reference data into cloud-native services, improving data freshness, scalability, and system reliability.
- •Optimized high-throughput backend services by tuning thread pools, connection pooling, Redis caching, and database queries, reducing P95 API latency by 35% while sustaining 3.5K requests per second at peak load.
- •Built centralized observability and monitoring using ELK Stack, Splunk, Grafana, and Snowflake, ingesting over two million daily events, improving MTTD by 40% and enabling real-time alerting for 99.9% SLA compliance.
- •Delivered HIPAA-compliant features including provider search with Elasticsearch achieving sub-200ms P99 latency on over 500K records, secure APIs, and PostgreSQL with row-level security, partnering closely with security and compliance teams.
- •Owned production reliability through CI/CD automation using Jenkins and GitHub and on-call rotations, maintaining 99.9% uptime and under two-hour MTTR; recognized with a Bravo Award for Kafka migration contributions.
Software Engineer
Jun 2021 – Sep 2021Deloitte
Full-Stack Development
- •Developed enterprise full-stack applications using Java, Spring Boot, Angular, and Next.js with a focus on performance, security, and maintainability.
- •Designed role-based backend APIs using NestJS and PostgreSQL, aligning implementations with internal privacy and compliance requirements.
- •Created Prometheus-based monitoring and alerting pipelines and integrated automated incident workflows with ServiceNow, improving system visibility, on-call response, and operational readiness.
- •Participated in agile ceremonies, authored low-level design documentation, and conducted peer code reviews to ensure adherence to engineering standards.
Software Engineering Intern
Jan 2021 – Jun 2021KPMG
Full-Stack Development
- •Built a secure internal risk assessment and vendor compliance platform using Python, Flask, React, and MongoDB.
- •Automated CI/CD pipelines via Azure DevOps, reducing deployment latency through parallel execution and build caching.
- •Developed secure REST APIs and optimized database operations to handle increased load while preserving auditability.
- •Automated compliance workflows, reducing manual auditing time by 70% and improving assessment throughput.
Education
MS in Computer Science and Engineering (AI/ML)
Aug 2024 – Dec 2025University at Buffalo
Buffalo, NY
B.Tech, Electronics and Computer Engineering
Jun 2017 – Jul 2021VIT University
Vellore, India
Awards & Certifications
Top 10%, PICOCTF Cybersecurity Competition
Carnegie Mellon University
2021
Data Structures and Algorithms, Top Scorer
NPTEL
2020
Featured Projects
Production-grade systems and ML applications built end-to-end
Technical Skills
Full-stack expertise across backend systems, cloud infrastructure, data engineering, and AI/ML
Languages
Core programming languages and scripting
Frontend Development
Modern web applications and responsive UI
Backend Development
Scalable APIs and microservices architecture
Databases
SQL, NoSQL, and distributed data stores
Data Engineering
Real-time streaming and batch processing pipelines
Cloud & DevOps
Cloud-native infrastructure and CI/CD automation
AI & Machine Learning
Deep learning, NLP, and generative AI
Concepts & Methodologies
Software engineering principles and practices
Get in Touch
I'm always open to discussing new opportunities, collaborations, or interesting projects.
Contact Information
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