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Manohar Paleti

Full Stack Engineer • Cincinnati, OH • M**************@gmail.com • +15******589 • linkedin/••••• • portfolio/•••••

Professional Summary

Full Stack Software Engineer with 4+ years delivering cloud-native applications across e-commerce, fintech and SaaS. Strong background in Java and Spring Boot microservices, React and TypeScript frontends, and AWS infrastructure (ECS, EKS, Lambda). Experience building high-throughput distributed systems (52K RPM order pipelines), improving latency and reliability, and integrating GenAI/RAG solutions into production workflows. Comfortable owning end-to-end delivery: architecture, CI/CD, observability and incident response.

Technical Skills

Programming Languages: Java,Python,TypeScript,JavaScript,C#
Frameworks and Libraries: Spring Boot,React,Angular,Django,Node.js,.NET,LangChain
Databases: PostgreSQL,MongoDB,MySQL,Redis,DynamoDB,S3
Cloud and DevOps: AWS EKS,AWS ECS,AWS Lambda,AWS SNS,Azure,GCP,Docker,Kubernetes,Terraform,Jenkins,GitHub Actions
Testing: JUnit,Selenium,PyTest,TDD
Tools and Methodologies: Agile
Observability & Monitoring: Prometheus,Grafana,New Relic,OpenTelemetry
Streaming & Messaging: Apache Kafka
AI and LLM and RAG: OpenAI API,Pinecone,RAG pipeline design,embedding models

Work Experience

PTC
Boston, MA
Full Stack Engineer
Jan 2025 – Present
Tech Stack: Spring Boot, React, GraphQL, AWS EKS, Terraform, OpenTelemetry, Jenkins, GitHub Actions, JUnit, Selenium
  • Re-engineered Spring Boot microservices concurrency and thread handling to sustain 100K concurrent users, cutting average API response latency by ~200ms and improving overall throughput.
  • Eliminated a 2.1s React page-load bottleneck by implementing code-splitting and lazy loading, reducing load time by 40% and increasing measured session duration by 22%.
  • Redesigned GraphQL schemas and introduced query batching for 15 client applications, reducing average API payload size by 25% and accelerating data delivery across the platform.
  • Built CI/CD pipelines with Jenkins and GitHub Actions incorporating JUnit and Selenium test suites, shortening deployment cycle time by 45% and reducing release incidents to near zero.
  • Codified AWS EKS deployments with Terraform and integrated OpenTelemetry tracing across services, reducing mean time to resolution by 30% and enabling same-day incident resolution.
  • Collaborated with product and client teams to prioritize platform reliability improvements, driving cross-team adoption of observability best practices and automated rollback procedures.
Hudson’s Bay Company
New York, NY
Software Engineer
Jan 2024 – Dec 2024
Tech Stack: Redis, Java, Angular, NgRx, AWS ECS, MongoDB, New Relic, Grafana
  • Architected Redis caching and Java thread-pool optimizations to scale order processing to 52K RPM during Black Friday, delivering a 40% throughput gain over prior peaks.
  • Built an Angular + NgRx bulk-import console that replaced a 4-hour manual catalog workflow, reducing update time to 8 minutes and eliminating ~95% of data-entry errors.
  • Re-platformed core services to AWS ECS with MongoDB across three regions, achieving ~40% better distributed throughput and consistent sub-100ms service response times.
  • Instrumented New Relic and Grafana with distributed tracing to surface service-level issues, cutting incident detection time by 50% and enabling proactive SLA alerts.
  • Defined real-time API contracts with mobile and web teams and contributed to API versioning strategy, helping improve cart-to-checkout conversion rate by a measured 15%.
  • Led load testing and production readiness activities for seasonal peaks, validating autoscaling behavior and reducing production performance regressions.
Cognizant Technology Solutions
Mumbai, IN
Software Engineer (Programmer Analyst)
Sep 2020 – Dec 2022
Tech Stack: Python, Django, React, TypeScript, Apache Kafka, Prometheus, Grafana, PyTest
  • Architected modular Python and Django fintech APIs with independent deployment patterns, enabling the banking platform to absorb 3x transaction volume spikes without degradation.
  • Delivered a React + TypeScript real-time analytics dashboard that replaced a 2-day manual reporting cycle, improving report accuracy by 61% and providing live visibility to managers.
  • Designed and implemented an Apache Kafka event-driven pipeline across six downstream consumers, reducing transaction processing latency by 45% and improving fault tolerance.
  • Integrated Prometheus and Grafana monitoring and built PyTest regression suites, enabling alert-driven incident response that consistently prevented SLA breaches.
  • Collaborated with QA and operations to automate deployment and regression testing, shortening release validation windows and reducing rollbacks.
  • Participated in architectural reviews and code improvements to ensure SOLID design principles and scalable service decomposition for high-throughput banking use cases.
Digital Eyecon Pvt Ltd
New Delhi, IN
Software Engineering Intern
Feb 2020 – Aug 2020
Tech Stack: WebSockets, Azure Kubernetes Service, Docker, xUnit, SQL indexing
  • Designed and built core CRM backend modules (patient intake, appointment scheduling, records management) as the sole backend engineer on a 4-person team.
  • Implemented REST APIs and data models to support CRM workflows, enabling front-end features and integrations with patient monitoring systems.
  • Improved database query performance by 35% through schema optimization and index restructuring across the patient records system.
  • Reduced real-time clinical alert sync latency from 5s to 200ms by implementing WebSocket-based communication between CRM and monitoring modules.
  • Delivered a containerized CRM deployment on Azure Kubernetes Service with automated test suites, increasing automated test coverage by 40%.
  • Collaborated with product and QA to triage defects and deploy hotfixes, reducing post-deploy rollbacks and improving production stability.
NY Software
IN Software

Projects

RAG-Powered Enterprise Knowledge Assistant | Apr 2025 – June 2025
Tools Used: Python, LangChain, OpenAI API, Pinecone, FastAPI, AWS S3, PostgreSQL
  • Built a retrieval-augmented generation system ingesting 10K+ internal documents into Pinecone vector store to enable semantic search with sub-500ms query response times.
  • Designed a multi-stage LLM pipeline with context reranking, citation grounding and hallucination guardrails, achieving 91% answer accuracy on a held-out evaluation set.
LLM-Powered Incident Triage and Runbook Automation | Jan 2025 – Mar 2025
Tools Used: Python, OpenAI API, PagerDuty Webhooks, AWS Lambda, DynamoDB, Slack API
  • Built an LLM-powered incident triage service ingesting PagerDuty alerts, classified severity using GPT-4, and posted structured summaries with suggested runbook steps to Slack.
  • Designed a prompt pipeline combining alert metadata, dependency graphs and historical context, reducing average engineer time-to-triage by 55%.
GenAI Pull Request Intelligence Platform | Oct 2024 – Dec 2024
Tools Used: Python, Node.js, OpenAI API, MongoDB, GitHub Webhooks
  • Built an LLM-powered code review service via GitHub webhooks, reducing manual PR review time by 60% and catching 45% more bugs before merge.
  • Designed a context-aware prompt pipeline feeding code diffs, file history and repo conventions to GPT-4, and stored severity-scored comments in MongoDB.

Education

University of Cincinnati
Master of Science in Information Technology • Cincinnati, OH • Jan 2023 – Apr 2024
Gitam University
Bachelor of Science in Computer Science • Visakhapatnam, India • 2022

Certifications

AWS Certified Developer – Associate — Amazon Web Services
Microsoft Certified: Azure Developer Associate (AZ-204) — Microsoft

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