AI, engineering, APIs, Node.js, Next.js, SQL, LLMOps

He is an AI and Data Engineering with over 3 years of experience. Currently, he is a Data Engineer at XXXX, where he serves as the primary technical authority for AI and Data within a transaction management platform serving SMEs across APAC. He designed and deployed an end-to-end agentic AI chatbot. He orchestrates the backend logic, defining communication protocols and agent behaviors in collaboration with senior frontend engineers. He also developed an AI-driven bank statement interpreter. He utilizes Large Language Models (LLMs) to transform unstructured data (PDFs, JPEGs, screenshots) into structured, database-friendly JSON, streamlining enterprise transaction management. He is leading the strategic migration of the company’s data infrastructure to Databricks, ensuring a scalable foundation for advanced analytics and machine learning. As the sole AI engineer, he owns the “Deployment-to-Database” journey, integrating complex AI workflows directly into the core Fintech product.

2.       What skill(s) / experience would you self-describe as strongest or specialist in?  

Strongest skills would be engineering and AI. He is highly proficient in the entire machine learning lifecycle, from data ingestion in Databricks to the training, optimization, and deployment of production-grade models. His background in Applied AI and Statistics allows him to navigate complex domains like Natural Language Processing (NLP) and Computer Vision with a deep understanding of the mathematical principles involved. Also, he is expert at building robust, secure APIs that serve as the interface between complex AI agents and the user-facing application, specialized in transaction management contexts. He specializes in the backend logic of Agentic AI, creating autonomous workflows that can reason through unstructured financial data and interact with external protocols. While his primary credibility lies in the backend, he is a “Unified Systems Engineer” who has successfully led front-to-back integrations, particularly where frontend components must interface with complex AI logic.

3.       Do you have the lists of key criteria’s according to the clients’ requirements?

He is an AI and Data Engineering with over 3 years of experience. He is expert in building production-ready Agentic AI systems. He has implemented pipelines that allow financial institution (FI) clients to communicate with internal APIs and real-time market data using natural language. He possesses a robust command of the required stack, including Node.js, Next.js, and Python (FastAPI/Express). He is proficient in both SQL and NoSQL databases, including PostgreSQL, MongoDB, and BigQuery. He has extensive experience developing ETL pipelines that ingest 50GB/day, ensuring low latency and scalability using Databricks and on-premises GPU servers. Moreover, he has spearheaded performance evaluator pipelines for AI agents and built auditable LLMOps frameworks on AWS and GCP to ensure governance and security for financial clients.