Senior Java Engineer | Microservices Architect | AI/ML Enthusiast
With 11+ years of experience building high-impact backend systems, I specialize in Java, Quarkus/Spring Boot, distributed systems, and now expanding into AI/ML & trading systems.
I build and lead full-stack microservice architectures—REST APIs, caching, event-driven systems, observability, and deployment at scale.
Highlight projects:
- Product Catalog Microservice (
productservice) — end-to-end architecture. - Driving School Platform (
drivingschool) — domain-driven design in action.
To prepare for senior roles (Tech Lead/SDE3) at top-tier companies, I document and code both core algorithmic fundamentals and system design patterns.
Repos include:
tech-interview-prep— DSA in Java + System Design (LLD/HLD)- Algorithms, data structures, design trade-offs, distributed patterns.
My next frontier: combining domain expertise with data science and AI—building tools for stock-market insights, NLP, and trading automation.
Upcoming project: ai-trading-agent (live-demo coming soon)
| Repo | Purpose | Link |
|---|---|---|
tech-interview-prep |
Curated DSA + System Design | https://github.com/vilasjadhav003/tech-interview-prep |
productservice |
Microservice architecture example | https://github.com/vilasjadhav003/productservice |
tradeReport |
Trade reporting engine (backend) | https://github.com/vilasjadhav003/tradeReport |
drivingschool |
(In progress) Business-app domain platform | https://github.com/vilasjadhav003/drivingschool |
(More AI/ML and architecture-playbook repos will be pinned soon.)
Languages: Java (primary), Python (for AI/ML)
Frameworks & Tools: Quarkus, Spring Boot, Vert.x, REST, Docker, Kubernetes, Elasticsearch, Apache NiFi
Concepts: Microservices, Event-Driven Architectures, Caching, Observability, Distributed Systems, System Design
AI/ML: Data Ingestion, Feature Engineering, NLP, LLM Integration, Trading Algorithms
Interview Prep: Data Structures & Algorithms, System-Design Patterns (LLD & HLD), BigTech style problem solving
- 📘 A system-design playbook repo: documenting high-scope HLD and low-level LLD (e.g., consistent hashing, event sourcing)
- 📊 An AI trading agent: ingesting stock data, building models, serving results via API/dashboard
- 📚 Daily exercise: solving algorithmic problems and writing clean, annotated Java solutions for review
- 💡 Building my business application stack: deploying microservices for real-world domain problems, integrating CI/CD, monitoring, and scaling.
- LinkedIn: https://www.linkedin.com/in/vilas-jadhav-9b0149129/
- Email: [email protected]
- GitHub: @vilasjadhav003
I’m a seasoned engineer who thrives at the intersection of robust backend systems and emerging AI/ML innovation.
Whether building a production-grade microservice fleet, designing scalable distributed systems, or coding clean algorithms for big-tech interviews—my work is about delivery, clarity, and impact.
Let’s build something scalable, smart, and resilient.