Praveen Mandadi — AI Researcher

I specialize in building high-performance, scalable backend systems using Spring Boot to create robust microservices and REST APIs. Leveraging both Java and Python, I design and implement enterprise-grade solutions that ensure seamless integration with modern data pipelines, including robust ETL processes, Kafka for event-driven architectures, and MongoDB for efficient data storage. I focus on developing maintainable, high-quality code while optimizing system performance and reliability. In addition to my Spring Boot expertise, I have extensive experience deploying machine learning models in Kubernetes environments, integrating them with backend systems, and implementing real-time monitoring and logging solutions using the ELK stack. I also leverage Prometheus and Grafana for system health tracking and performance analytics. My work is centered around creating end-to-end solutions that support data-driven decision-making and continuous improvement in production environments. I have hands-on experience with AWS cloud infrastructure, managing services like EC2, EKS (Elastic Kubernetes Service), CloudWatch, and EBS for scalable compute resources and monitoring. I ensure secure and efficient deployment by configuring IAM roles, managing EC2 instances, optimizing storage with EBS volumes, and setting up CloudWatch for logging and metrics collection. My responsibilities include managing cloud resources, orchestrating containerized applications with EKS, ensuring system security, and automating infrastructure provisioning, enabling reliable, scalable, and cloud-native applications.

Stackforce AI infers this person is a Backend-heavy Fullstack Engineer with expertise in SaaS and cloud-native solutions.

Location: Houston, Texas, United States

Experience: 11 yrs 7 mos

Skills

Spring Boot
Microservices
Agile Methodologies
Aws
Kubernetes
Elasticsearch
Spring Mvc

Career Highlights

Expert in building scalable backend systems with Spring Boot.
Proficient in deploying machine learning models in Kubernetes.
Strong experience in AWS cloud infrastructure management.

Work Experience

Siemens

Artificial Intelligence Engineer (1 yr 6 mos)

Senior Java Developer (2 yrs 1 mo)

Fujitsu Network Communications

Senior Application Developer (2 yrs 8 mos)

Terralogic Inc. (Fujitsu Network Communications)

Technical Lead (3 yrs)

Fujitsu

Senior Java Software Engineer (3 yrs)

Terralogic Inc. ( Cisco )

Software Engineer 2 (1 yr 4 mos)

CISCO & YATRAGINIE

Software Engineer (4 yrs)

Terralogic Inc.

Software Engineer (3 yrs)

Education

Bachelor of Engineering (B.E.) at PRATHYUSHA ENGINEERING COLLEGE

Bachelor of Engineering at invalid562524

Praveen Mandadi

AI Researcher

Houston, Texas, United States11 yrs 7 mos experience

AI EnabledHighly Stable

Key Highlights

Expert in building scalable backend systems with Spring Boot.
Proficient in deploying machine learning models in Kubernetes.
Strong experience in AWS cloud infrastructure management.

Stackforce AI infers this person is a Backend-heavy Fullstack Engineer with expertise in SaaS and cloud-native solutions.

Contact

Skills

Core Skills

Spring BootMicroservicesAgile MethodologiesAwsKubernetesElasticsearchSpring Mvc

Other Skills

AI-Powered License ManagementGitHub CopilotRESTful APIsKafkaDatadogGitLab CI/CDAWS ECSAI-enhanced software engineeringCI/CD pipelinesAI modelsMicroservices architectureOAuth 2.0PrometheusGrafanaDocker

About

Experience

11 yrs 7 mos

Total Experience

2 yrs 9 mos

Average Tenure

1 yr 6 mos

Current Experience

Siemens

2 roles

Artificial Intelligence Engineer

Dec 2024 – Present · 1 yr 6 mos

AI-Powered License Management: Architected a License Management System using GitHub Copilot with Claude Sonnet 4.5/4.6 and GPT-5.2 Codex; authored full functional requirements, API contracts, and acceptance criteria for development and testing teams — accelerating feature delivery by 40% and eliminating requirement ambiguity across sprints.
Copilot Agent Mode Adoption: Drove team-wide adoption of Copilot planning and agent mode across the full SDLC — conducted internal workshops, created prompt engineering guidelines, and defined best practices, cutting feature development time by 35% and shipping sprint goals consistently ahead of schedule.
AI-Assisted Integration Testing: Used Copilot agent mode to generate and iterate integration and regression test suites for Spring Boot microservices, raising coverage from 62% to 90%+ and cutting manual QA effort by 3 days per sprint — significantly improving release confidence.
Datadog BitsAI Debugging: Adopted Datadog BitsAI for intelligent log analysis, anomaly triage, and root cause correlation across distributed services; combined with Copilot agent mode to resolve production issues in hours instead of days — reducing MTTR by 50%.
GitLab CI/CD to AWS ECS: Built fully automated GitLab CI pipelines using Claude Sonnet 4.5/4.6 covering build, unit tests, security scans, and zero-downtime ECS deployments — compressing release cycles from days to under 2 hours, enabling multiple production releases per week.
Microservices Architecture & API Design: Designed and delivered 8+ RESTful and event-driven microservices using Java 17/Spring Boot and Kafka, applying DDD principles and circuit breaker patterns to serve 20,000+ concurrent users with high availability.
Cross-Team Technical Leadership: Served as primary technical point of contact for 3 agile squads; conducted architecture reviews, sprint planning, and code walkthroughs — reducing post-release defects by 30%.

AI-Powered License ManagementGitHub CopilotSpring BootRESTful APIsMicroservicesKafka+3

Senior Java Developer

May 2024 – Present · 2 yrs 1 mo

Innovative Full-Stack Developer specializing in AI-enhanced software engineering and microservices architecture. Leveraging advanced AI models (GPT-4.1, Claude 3.7 Sonnet, Gemini 2.0) to transform development workflows and deliver enterprise solutions with unprecedented efficiency.
Architected a comprehensive license management platform using Spring Boot microservices, employing strategic AI prompt engineering to accelerate development by 30%. My implementation included:
Financial processing systems optimized with GPT-4.1, improving reconciliation accuracy by 25%
Hierarchical user management leveraging multiple AI models for enhanced security patterns
Predictive notification engine created through customized prompts across o3-mini and GPT-4o
Interactive dashboards built with AI-assisted Python/Dash, reducing development time by 40%
My technical approach combines cloud-native expertise (AWS ECS/EKS) with AI-generated infrastructure templates, resulting in 35% improved deployment reliability. I've established robust CI/CD pipelines utilizing Claude 3.7 Sonnet Thinking for test generation, achieving 90%+ code coverage and 40% faster deployments.
Key strengths include developing comprehensive test suites with AI-generated scenarios, designing RESTful APIs through model-specific prompt strategies (reducing integration issues by 45%), and creating technical documentation by strategically selecting the optimal AI model for each component.
I excel in evaluating AI outputs against business requirements and strategically selecting appropriate models for specific development challenges, consistently delivering solutions that exceed expectations in quality, performance, and time-to-market.

AI-enhanced software engineeringSpring BootAWS ECSCI/CD pipelinesRESTful APIsAWS

Fujitsu network communications

Senior Application Developer

Jul 2021 – Mar 2024 · 2 yrs 8 mos · Bengaluru, Karnataka, India · On-site

Led a team of 28 in designing microservices architecture, enhancing system scalability and performance by 35%.
Developed and deployed high-performance RESTful APIs using spring boot, achieving sub-millisecond response times.
Implemented OAuth 2.0 security pattern and JWT, enhancing application security and compliance.
Developed and streamlined deployment pipelines using Spring Boot to automate AI/ML model deployment, scaling, and resource allocation on Kubernetes, reducing manual intervention and improving operational efficiency.
Proficient in containerizing applications using Docker, optimizing images, and managing Docker Compose for multi-container environments.
Expertise in managing Kubernetes applications with Helm, including creating, deploying, and maintaining Helm charts for scalable and reliable deployments.
Orchestrated and managed Kubernetes clusters, including deployment, scaling, and maintenance of containerized applications using Helm charts, kubectl, and Kubernetes API.
Integrated monitoring (Prometheus, Grafana) and centralized logging (ELK, Fluentd) for proactive issue resolution and performance tracking in production environments.
Built and deployed scalable Python-based microservices using FastAPI for high-performance REST APIs, ensuring low latency and efficient handling of concurrent requests.
Configured and managed AWS EC2 instances, Load Balancers (ELB), and EKS clusters, optimizing resource usage by 40%.
Automated CI/CD pipelines using Jenkins, reducing deployment time by 50%.
Developed Spring Boot microservices and implemented user authentication using Spring Security
Established CI/CD pipelines for on-premises and AWS deployments, reducing manual deployment errors by 30%
Leveraged Apache Kafka for real-time data processing, enhancing the system's ability to handle high-throughput data streams and ensuring near-instantaneous event processing.

Microservices architectureRESTful APIsOAuth 2.0KubernetesPrometheusGrafana+1

Terralogic inc. (fujitsu network communications)

Technical Lead

Jul 2018 – Jul 2021 · 3 yrs · Bengaluru, Karnataka, India · On-site

Led the development of microservices architecture and RESTful APIs, enhancing scalability and security measures.
Implemented transaction management in Spring Boot applications using @Transactional for data consistency and reliability.
Optimized cloud deployment strategies on AWS, resulting in a 30% cost reduction and improved resource utilization.
Mentored and led a team of 10 developers, improving code quality and reducing bug incidents by 25%.

Microservices architectureSpring BootAWSDockerKubernetesMicroservices

Fujitsu

Senior Java Software Engineer

Jul 2018 – Jul 2021 · 3 yrs

High-Performance Analytics: Built Spring Boot + Elasticsearch services for sub-second queries across 10B+ events; implemented custom scoring pipelines and index lifecycle management, cutting average response time from 8s to 280ms.
ML Observability UI: Designed Angular dashboards with embedded Grafana and D3.js visualizations for real-time ML model drift, feature importance shifts, and prediction confidence — enabling 4x faster degradation detection and response.
Unified API Layer: Consolidated 6 VAX platform endpoints into a single versioned RESTful gateway with request routing, rate limiting, and centralized error handling — reducing downstream integration effort by 40% and cutting consumer onboarding from 2 weeks to 3 days.
Event-Driven Notification System: Built async notification microservice on Spring Boot + Kafka processing 2M+ events/day with real-time alerting via email, Slack, and PagerDuty integrations and configurable routing rules.
Security Hardening: Instituted OWASP-aligned security reviews, integrated SAST scanning into Jenkins pipelines, and remediated 120+ critical vulnerabilities ahead of SOC 2 audit.

Spring BootElasticsearchAngularJenkins

Terralogic inc. ( cisco )

Software Engineer 2

Feb 2017 – Jun 2018 · 1 yr 4 mos · Bengaluru, Karnataka, India · On-site

Developed robust solutions for the "Catalyst Migration tool" project, meeting client requirements for functionality and performance.
Led the UI team in designing functional requirements and Dashboard Design.
Mentored less-experienced staff members and provided guidance in deploying Stand-alone flask restful in production.
Analyzed data to coordinate system installations and modifications.

JavaSpring Boot

Cisco & yatraginie

Software Engineer

Jan 2014 – Jan 2018 · 4 yrs

High-Concurrency Backend: Built Spring Boot microservices handling 20,000+ concurrent users with 99.95% SLA across 3 consecutive peak seasons, leveraging connection pooling, async processing, and horizontal auto-scaling on AWS EC2.
Database Performance: Profiled and rewrote 50+ slow MySQL/Oracle queries, introduced Redis caching and read replicas — cutting page load times by 40% and API latency by 45% under production load.
CI/CD Transformation: Architected Jenkins pipelines from scratch with automated builds, unit tests, coverage gates, and artifact promotion — reduced deployment cycles by 70%, from multi-day manual releases to automated hourly builds.
Payments & Reliability: Integrated Stripe/PayPal on AWS EC2/RDS processing $50M+ annually with 99.99% transaction consistency via idempotency keys, retry logic, and dead-letter queue handling.

JavaSpring Boot

Terralogic inc.

Software Engineer

Jan 2014 – Jan 2017 · 3 yrs · Bengaluru, Karnataka, India · On-site

Developed scalable microservices using Spring Boot, leading to a 50% improvement in system performance and reliability.
Optimized RESTful APIs, reducing response times by 40% and supporting up to 20,000 concurrent users.
Enhanced application security by implementing OAuth 2.0 and JWT, achieving 100% compliance with industry security standards.
Spearheaded the optimization of cloud infrastructure on AWS (EC2, S3, RDS), resulting in a 35% reduction in operational costs and a 25% increase in efficiency.
Automated deployment processes with Jenkins, Docker, and Kubernetes, reducing deployment times by 70% and increasing deployment frequency by 50%.
Provided technical leadership and mentorship to a team of 10 developers, improving code quality by 30% through regular code reviews and best practice training sessions.
Implemented Apache Kafka for real-time data processing and event-driven architecture, enabling the system to handle millions of events daily with near-zero latency.

JavaSpring MVC