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Senior AI/ML Engineer with 11+ years of experience building production-grade enterprise AI/ML and Generative AI platforms on AWS. Deep expertise in LLMs, RAG, prompt engineering, and agentic workflows using LangChain/LangGraph and vector databases. Experienced in end-to-end MLOps and distributed data pipelines—training, deployment, monitoring, evaluation, and governance. Proven track record delivering secure, scalable microservices and AI solutions across finance, telecommunications, and healthcare domains.…Senior AI/ML Engineer with 11+ years of experience building production-grade enterprise AI/ML and Generative AI platforms on AWS. Deep expertise in LLMs, RAG, prompt engineering, and agentic workflows using LangChain/LangGraph and vector databases. Experienced in end-to-end MLOps and distributed data pipelines—training, deployment, monitoring, evaluation, and governance. Proven track record delivering secure, scalable microservices and AI solutions across finance, telecommunications, and healthcare domains.

Sruthi N

AI Engineer, Data Scientist, Data Engineer, +2

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Senior AI/ML Engineer with 11+ years of experience building production-grade enterprise AI/ML and Generative AI platforms on AWS. Deep expertise in LLMs, RAG, prompt engineering, and agentic workflows using LangChain/LangGraph and vector databases. Experienced in end-to-end MLOps and distributed data pipelines—training, deployment, monitoring, evaluation, and governance. Proven track record delivering secure, scalable microservices and AI solutions across finance, telecommunications, and healthcare domains.…Senior AI/ML Engineer with 11+ years of experience building production-grade enterprise AI/ML and Generative AI platforms on AWS. Deep expertise in LLMs, RAG, prompt engineering, and agentic workflows using LangChain/LangGraph and vector databases. Experienced in end-to-end MLOps and distributed data pipelines—training, deployment, monitoring, evaluation, and governance. Proven track record delivering secure, scalable microservices and AI solutions across finance, telecommunications, and healthcare domains.

Available to hire

Senior AI/ML Engineer with 11+ years of experience building production-grade enterprise AI/ML and Generative AI platforms on AWS. Deep expertise in LLMs, RAG, prompt engineering, and agentic workflows using LangChain/LangGraph and vector databases.

Experienced in end-to-end MLOps and distributed data pipelines—training, deployment, monitoring, evaluation, and governance. Proven track record delivering secure, scalable microservices and AI solutions across finance, telecommunications, and healthcare domains.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

Work Experience

Sr. AI/ML Engineer at Fidelity Investments

December 1, 2024 - Present

Designed and delivered an enterprise Generative AI / fraud intelligence platform on AWS to modernize fraud investigation workflows, decision support, and enterprise knowledge discovery. Built cloud-native RAG pipelines using semantic search and vector embeddings to retrieve historical fraud cases, regulatory documents, and investigation knowledge. Developed production-grade LLM applications for fraud summarization, contextual reasoning, documentation, and recommendation generation. Implemented AI agent workflows for multi-step fraud investigations including knowledge retrieval, transaction analysis, and analyst recommendations. Built Model Context Protocol (MCP) integrations and reusable MCP servers/clients/tools to securely connect agents with enterprise APIs, databases, and data sources with authentication/authorization/guardrails and auditability. Exposed AI inference, semantic search, agent tools, and recommendations via FastAPI-based secure REST microservices. Established MLOps an

AI/ML Engineer at Cox Communication

October 1, 2021 - November 30, 2024

Architected and implemented enterprise AI/ML solutions on AWS supporting customer intelligence, predictive analytics, and operational automation across telecommunications platforms. Built scalable FastAPI services for ML inference and intelligent automation. Developed production-ready models for customer behavior analysis, service usage prediction, anomaly detection, and network performance optimization. Implemented semantic search and knowledge retrieval with embeddings (including graph-based reasoning) to improve customer support automation. Built event-driven AI processing with Apache Kafka and AWS services for asynchronous and near real-time analytics. Established MLOps pipelines for training, deployment, experiment tracking, monitoring, and lifecycle management. Implemented model evaluation practices covering quality, explainability, and production readiness; delivered secure cloud-native containerized microservices and mentored teams on AI architecture and ML engineering best pra

Data Scientist at Johnson & Johnson

July 1, 2019 - September 30, 2021

Developed end-to-end machine learning and predictive analytics solutions on AWS to modernize healthcare analytics and operational reporting. Built data ingestion, transformation, and preprocessing pipelines using Python, SQL, S3, and AWS Glue. Performed EDA and feature engineering with Pandas/NumPy/SQL to identify trends, anomalies, and predictive patterns. Developed supervised models (classification/regression/forecasting) using Scikit-learn, TensorFlow, and XGBoost, plus unsupervised/anomaly detection for unusual operational patterns. Implemented distributed processing with PySpark and Amazon EMR. Used SageMaker for training, evaluation, batch inference, and deployment with artifacts stored in S3. Added model validation and performance evaluation (cross-validation, precision/recall/F1, ROC-AUC, feature importance) and automated training/validation/inference workflows. Collaborated with stakeholders to translate analytical requirements into scalable, reliable ML solutions.

Python Developer at Sam's Club

March 1, 2016 - March 31, 2019

Built Python-based data processing and analytics solutions supporting retail sales analytics, inventory optimization, pricing analysis, and business intelligence at enterprise scale. Implemented ETL and data integration pipelines using Python, Azure Data Factory, Alteryx, SQL, Oracle, and Azure Data Lake Storage. Conducted EDA and RCA using Pandas/NumPy/SQL to identify sales trends, inventory shortages, pricing anomalies, and purchasing patterns. Developed predictive analytics and ML models for demand forecasting, segmentation, inventory planning, and sales prediction using Scikit-learn, XGBoost, TensorFlow, and PyTorch. Created Power BI dashboards using star/snowflake schema modeling and DAX for operational KPIs; automated data validation and scheduled batch processing to improve quality and reduce manual effort. Partnered with business and data engineering teams to deliver scalable analytics for merchandising and supply chain decision-making.

Data Warehouse Developer at Chubb Insurance

August 1, 2014 - April 30, 2016

Developed Python- and SQL-based data processing solutions integrating policy, claims, underwriting, and treasury data across enterprise systems to support insurance operations, regulatory reporting, risk analytics, and financial reporting. Automated recurring regulatory/liquidity/operational reports using Python and SQL, reducing manual processes and improving reporting accuracy. Designed and optimized SQL queries/stored procedures and extraction workflows across Oracle and Hadoop (Hive) to create validated datasets for BI and enterprise reporting. Built Tableau and Power BI dashboards for liquidity, cash flow, claims, underwriting performance, and KPIs. Collaborated with analysts and QA for validation, reconciliation, and UAT to ensure compliance and data integrity.