Ayush Bhatt

Software Engineer

Bengaluru, Karnataka, India8 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Expert in architecting scalable fintech platforms.
Proven track record in AI-driven data solutions.
Strong collaborative skills in cross-functional teams.

Stackforce AI infers this person is a Fintech Full-Stack Software Developer with expertise in AI and data-driven solutions.

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Skills

Core Skills

Backend Engineering & Api ArchitectureProblem Solving & Algorithmic ThinkingData AnalysisWeb Development

Other Skills

JavaSpring BootZeebeService ContractsDigital AutomationFeature RolloutRisk ControlBulk ProcessingSQSFinancial ComputationPython (Programming Language)DOCKERAIData ScienceML Pipeline

About

Results-driven Software Developer at Rupeek Fintech with a strong foundation in Computer Science, Full-Stack Engineering, and AI-driven systems, specializing in building scalable, event-driven fintech platforms. Proven experience architecting end-to-end workflows using Java Spring Boot, Zeebe, and cloud-native services, delivering production-grade solutions that directly impact customer experience and operational efficiency. Known for driving complex integrations across lenders, payment systems, and third-party providers while maintaining backward compatibility and platform resilience. Adept at translating ambiguous business requirements into robust, observable, and secure systems, from mechanized e-Sign pipelines to bulk financial processing and controlled feature rollouts. Thrives in fast-paced environments by collaborating closely with product, QA, and cross-functional teams to ship reliable solutions at scale.

Experience

8 mos

Total Experience

8 mos

Average Tenure

8 mos

Current Experience

Rupeek

2 roles

Software Developer

Sep 2025 – Present · 8 mos · On-site

End-to-End Workflow Architecture & Delivery: Architected and delivered the part-release slot booking capability using Java Spring Boot and Zeebe, designing new workflows, DTO layers, and an order-level data model. Integrated Salesforce ticketing to enable 500+ customers to successfully book slots within the first two weeks, dramatically improving operational throughput.
Lender-specific Platform Integrations: Led part-release integration for lender SIB, building Zeebe orchestration pipelines, service contracts, and compatibility layers. Ensured seamless onboarding without impacting full-release workflows or customer journeys.
Digital Automation: Built an e-Sign pipeline linking payment events and signing providers for a paperless, compliant document execution for customers and lenders.
Feature Rollout & Risk Control: Enhanced platform resilience via Flag smith city-wise rollouts. Implemented renewal blocking (cityId + loanRequestId), and rebate cancellation APIs to control feature exposure and mitigate risk.
Scalable Bulk Processing Systems: Designed and implemented a bulk file upload system that validates GL IDs, publishes verified documents to SQS, and uses authenticated data as the source of truth for downstream processing—enabling scalable and reliable bulk operations.
Financial Computation & Data Integrity: Built automated interest flows for unsecured components using validated GL IDs, ensuring accurate computations and consistent data across systems.
Distributed Workflow Orchestration: Integrated Zeebe-based workflows with SQS, payment platforms, and third-party providers, accelerating feature delivery while improving system resilience and operational visibility.

Backend Engineering & API ArchitectureProblem Solving & Algorithmic Thinking

Software Developer Intern

May 2025 – Sep 2025 · 4 mos · On-site

Preprod corp

Data Analyst And Web Developer

Nov 2023 – May 2024 · 6 mos · Bengaluru, Karnataka, India · Remote

AI & Data Research Leadership: Conducted deep-dive research across Artificial Intelligence, Machine Learning, and Data Science domains, translating academic and industry insights into actionable solutions that supported data-driven decision-making.
End-to-End ML Pipeline Optimization: Engineered and optimized scalable Data and ML pipelines for food demand forecasting, efficiently processing 100K+ data samples and achieving a strong predictive performance with RMSE of 63.
Analytics, Visualization & Model Tracking: Built interactive Power BI dashboards and implemented DVC and MLflow for robust experiment tracking and real-time model monitoring, improving transparency and reproducibility of ML workflows.
Full-Stack Data Product Development: Developed and deployed data-centric web applications using Flask, including automated invoice and report generation systems and a CRM platform supporting 3 hospitals and 30+ enterprise clients.

Python (Programming Language)DOCKERData AnalysisWeb Development