Farhan Mallick

About Farhan Mallick

I’m an AI Engineer and Solutions Architect passionate about turning raw data into intelligent, measurable, and compliant AI systems.Over the past 5+ years, I’ve built and deployed enterprise-grade GenAI and cloud data platforms that help businesses in healthcare, insurance, and IoT make smarter, faster, and more reliable decisions. My work bridges machine learning, LLM orchestration, and data engineering — so that innovation actually reaches production.At Capgemini, I’ve led the design and delivery of: • LLM & RAG pipelines using LangChain, Azure OpenAI, and Databricks for document intelligence and chatbot systems. • Cloud-native ETL and MLOps frameworks using Azure Data Factory, Kafka, and Airflow, cutting data latency by 45% and improving prediction accuracy by 30%. • Containerised AI services with GitLab, Docker, and Kubernetes, increasing deployment frequency by 50%.My focus is always measurable impact scalable pipelines, governed data, and transparent AI models built to comply with HIPAA and FDA-aligned standards.I thrive at the intersection of AI Engineering, Data Science, and Solution Architecture — designing systems that are fast, explainable, and production-ready.Currently open to senior roles in AI Engineering, Data Science, Data Engineering, or AI Solution Architecture, where I can design LLM, GenAI, and cloud analytics pipelines that drive ROI and responsible AI adoption.

Experience

1. Associate Consultant

   Capgemini

   May 2021 — Present · Mumbai, IN

   Designed RAG (Retrieval-Augmented Generation) chatbots using LangChain, Transformers, and OpenAI APIs, enabling 90%+ accuracy in PDF and document retrieval. • Developed OCR pipelines (Python, Tesseract, OpenCV) for multilingual UI validation, cutting manual QA effort by 70%. • Built Azure Data Factory + Databricks ETL pipelines to centralize operational data; achieved 45% faster data availability. • Deployed containerized AI microservices (Docker, Kubernetes, GitLab CI/CD), boosting release frequency by 50% and reducing errors in production. • Integrated ELK + AppDynamics monitoring, improving system observability and reducing downtime. • Delivered FDA-compliant AI testing frameworks with 100% unit-test coverage, ensuring regulatory audit readiness. • Created Power BI dashboards for quality analytics, enabling 30% faster QA decision-making. • Optimized Airflow pipelines for real-time ingestion, reducing data lag by 35%.

Education

• Rizvi College of Engineering

  Bachelor's degree

  2015 — 2019