Headline

AI Architect

About

AI Architect and Data Science professional with 8+ years of experience building scalable AI/ML solutions across financial crime analytics, regulatory compliance, risk modeling, NLP, and GenAI applications. Skilled in designing end-to-end ML pipelines, anomaly detection systems, LLM-powered NLP workflows, and production-grade scoring platforms using Python, SQL, Databricks, Microsoft Fabric, AWS SageMaker, and MLFlow. Experienced in deep learning, model validation, feature engineering, risk analytics, and governance frameworks, with a strong focus on translating complex analytics into business impact through stakeholder collaboration and scalable architecture design.

Location

Bengaluru

AI stack

claude

hugging face

langchain

langgraph

langsmith

Cohere

Work experience

AI Architect at Nagarro, Aug 2025 - Present · 1 yr 2 mos, ● Developed a scalable Customer Satisfaction Risk(CSR) scoring platform on Databricks and Microsoft Fabric leveraging ML/DL capabilities for case-level risk monitoring. ● Built scalable feature engineering pipelines integrating structured data and LLM-based NLP attributes, improving predictive signal quality by 15%. ● Implemented feature evaluation frameworks covering exploratory analysis, selection logic, and correlation assessment to strengthen model robustness and feature reliability. ● Created LLM-based NLP workflows to process chronological texts, extract behavioral signals, translate multilingual content, and generate unstructured features for risk analysis, improving model performance by 20%. ● Designed production-grade batch scoring pipelines to generate daily CSR scores by orchestrating feature groups, model weights, and inference logic. ● Defined solution architecture, pipeline documentation, feature store structures and MLFlow lifecycle integration in collaboration with cross-functional teams to enable downstream analytics and long-term maintainability.

Manager: AI & Analytics at HSBC, Oct 2022 - Aug 2025 · 2 yrs 11 mos, ● Designed and implemented Deep Learning based auto-encoders for Anomaly Detection in trade transactions, reducing false positives by 30% and enhancing risk detection capability to safeguard the bank from regulatory censure and fines. ● Conducted extensive exploratory data analysis (EDA) and feature engineering on large datasets, fine-tuned models using advanced regularization and hyper-parameters tuning, improving model convergence and performance. ● Implemented advanced statistical techniques to compute anomaly thresholds, identifying high-risk trades and reducing manual review time by 25%. ● Established robust model monitoring frameworks, including data monitoring and performance tracking using KPIs such as model stability index, characteristic stability index, anomaly percentage, and reconstruction error, ensuring consistent model performance. ● Contributed to advanced NLP-driven communication surveillance capability, strategically enhancing bank's risk detection by 3 folds. ● Performed model risk management responsibilities, encompassing model validation, inventory management, governance protocols, and reporting, ensuring compliance with multifaceted regulatory requirements and internal audit standards. ● Led end to end experimentation life-cycle: hypothesis design, roll-out strategy, statistical analysis and impact assessment using tools like SQL, Python and statistical libraries.

Business Intelligence Analyst at Empower, May 2020 - Sep 2022 · 2 yrs 5 mos, ● Worked on advanced credit risk modeling solutions, leveraging machine learning algorithms and statistical analysis to strengthen business decision and risk assessment. ● Implemented comprehensive data preparation pipelines, with domain specific feature engineering and extraction techniques to prepare high quality data resulted in enhanced model performance by 15%. ● Worked on an unsupervised customer segmentation model to optimize financial plan recommendations, improving personalization and decision-making. ● Contributed in NLP-based model to analyze customer-raised event’s sentiment by implementing pipeline for test cleaning, preprocessing, word embedding to extract deeper insights. ● Detected trend anomalies and outliers using statistical profiling and presented insights to business stakeholders through visualization and reports.

Software Engineer - ML at ZYCUS INFOTECH, Jul 2017 - Apr 2020 · 2 y 9 mo, India, ● Worked on supplier performance analysis using SQL,classical machine learning, advanced analytics and provided insights using visualization tools. ● Conducted customer analytics to derive actionable insights, improved customer engagement, and optimized business strategies.

Education

Bachelor of Technology, Computational Science, biju patnaik university of technology