s
sourabh_957

Sourabh

@sourabh_957

Java Spring Boot and Kafka Backend Engineer with AI Integration

Inde
Hindi, Anglais
Certaines informations sont présentées en anglais.
À propos de moi
Java backend engineer with 4+ years of production experience building Spring Boot APIs, Kafka pipelines and Redis/PostgreSQL systems for lending and logistics platforms. Results: 40% lower inter-service latency, 45% faster payment reconciliation, and services handling 400K+ partner events a day. I also add AI to existing backends: document Q&A (RAG), AI agents that call your APIs, and LLM workflows with guardrails, tests and cost control. Tell me what's slow, broken or missing, and I'll scope a clear fix.... Plus d’infos

Compétences

s
sourabh_957
Sourabh
hors ligne • 
Temps de réponse moyen de 1 heure

Voir mes services

Intégrations IA
I will build and integrate ai agents, rag, and llm workflows
De90 $US / projetPlus de détails
Aide / Consultation
I will audit kafka consumer lag and give you a prioritized fix plan
De60 $US / projetPlus de détails

Portfolio

Expérience professionnelle

StatusNeo

Digital Product Engineering Consultant

StatusNeo • Temps plein

Dec 2025 - Aug 2026 • 8 mos

• ML Model Integration Service: let the Credit-Decision-Service call ML models directly, removing the Data-Fetcher-Service hop and cutting inter-service latency by 40%. • Configuration and rule platform (Spring Boot, MongoDB) for event-driven ML decisioning: 300+ configs, 70% less model-onboarding effort, 25% faster credit decisions. • AI-augmented development: Claude Code with MCP servers (Grafana, Atlassian, custom) took features from design to tested code in under 24 hours.

Porter

Software Development Engineer II

Porter • Temps plein

Jul 2022 - Nov 2025 • 3 yrs 4 mos

• Rewards and Recognition platform: 400K+ partner events a day, Redis sorted-set leaderboards, 600K drivers engaged, +3% fulfillment at Diwali peak. • AWS to GCP migration; owned backend deployments on GKE and Cloud Functions. • Configurable rule engine (400-500 configs): 60% fewer unfair partner penalties, zero-downtime rollout. • Kafka producers and consumers plus a Kafka Connect JDBC sink pipeline for near-real-time sync across services. • Payment reconciliation: Redis caching and PostgreSQL tuning made it 45% faster, preventing about INR 2.5 crore a year in leakage.

Samsung

Software Development Intern

Samsung • Temps plein

Jan 2022 - Jun 2022 • 5 mos

• Neural Processing Unit (NPU) team. • Built single-branch and multi-branch Jenkins pipelines in Groovy to automate building, testing and deploying models.