Veejay Garalde

Senior AI & Data Engineer with 8+ years of experience designing and delivering AI-driven applications, machine learning solutions, and large-scale data platforms. Experienced in building Retrieval-Augmented Generation (RAG) systems, intelligent document processing solutions, AI-powered search platforms, and distributed data pipelines using Python, Azure OpenAI Service, LangChain, LangGraph, Apache Spark, Kafka, Kubernetes, AWS, and Microsoft Azure. Strong background in architecting scalable AI and data systems, integrating machine learning into production environments, and developing cloud-native solutions that support business-critical workflows and data-driven decision-making.

Senior AI & Data Engineer at Kensho Technologies (2023-08 – 2026-05)

Kensho Extract – AI-Powered Financial Document Intelligence Platform

• Architected enterprise-grade AI document intelligence systems that transformed unstructured financial reports, regulatory filings, earnings transcripts, and research documents into structured and searchable knowledge assets.
• Designed and implemented large-scale Retrieval-Augmented Generation (RAG) pipelines integrating OCR, document understanding, semantic retrieval, vector search, and LLM-powered reasoning for financial question-answering workflows.
• Built AI-powered search and document copilot capabilities using Azure OpenAI Service, LangChain, Azure AI Search, Elasticsearch, and vector databases, enabling semantic search and knowledge discovery across millions of financial documents.
• Developed advanced NLP and information extraction services for entity recognition, document classification, metadata enrichment, relationship extraction, and intelligent search workflows.
• Engineered high-throughput data pipelines and lakehouse-style data processing architectures using Python, Apache Spark, Kafka, PostgreSQL, and cloud storage services to process, transform, and index large-scale financial document datasets for downstream AI and analytics applications.
• Designed hybrid retrieval architectures combining Azure AI Search, vector similarity search, metadata filtering, semantic reranking, and keyword search to improve retrieval precision and contextual relevance.
• Developed distributed AI microservices and serverless workflows using Python, FastAPI, gRPC, and Azure Functions supporting document ingestion, extraction, indexing, validation, and retrieval workflows.
• Optimized AI inference and document processing performance through asynchronous execution, distributed processing, caching mechanisms, and retrieval optimization.
• Containerized AI services with Docker and deployed production workloads on Kubernetes, Azure Kubernetes Service (AKS), AWS, and Microsoft Azure.
• Collaborated with product managers, financial analysts, and engineering teams to deliver enterprise AI solutions for financial intelligence and research platforms.

ML Engineer at Luma Financial Technologies (2021-01 – 2023-07)

Luma Creation Hub – Structured Product Pricing & Analytics Platform

• Developed machine learning and predictive analytics solutions for structured product pricing and investment analytics.
• Built scalable data pipelines processing market data, portfolio information, and financial datasets.
• Trained and optimized machine learning models using Python, Scikit-learn, and XGBoost for forecasting and risk analysis.
• Developed FastAPI services and REST APIs for model inference and analytics delivery.
• Designed distributed analytics workflows and cloud-native services on AWS and Microsoft Azure.
• Automated data validation, monitoring, and deployment processes using Docker and Kubernetes.

Data & ML Engineer at ComplyAdvantage (2017-11 – 2020-10)

Financial Crime Intelligence Platform

• Developed real-time transaction monitoring and risk intelligence pipelines using Apache Kafka and Spark Streaming.
• Built large-scale data processing workflows supporting AML compliance and financial crime investigations.
• Developed anomaly detection models to identify suspicious transaction patterns and improve fraud detection.
• Engineered distributed data processing systems and microservices using Python and Protobuf.
• Built ETL and data enrichment pipelines supporting risk scoring and investigative analytics.
• Deployed containerized applications using Docker, Kubernetes, and AWS.

Bachelor of Science in Computer Science – Sichuan University (2013-09 – 2017-06)