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Hi, I’m Meghana Reddy Manda. I’m a results-driven AI/ML Engineer with 4+ years of experience architecting and deploying production-scale machine learning and generative AI solutions across finance, healthcare, and enterprise domains. I specialize in building LLM-powered applications, RAG pipelines, fraud detection, and personalization systems that boost efficiency, reduce costs, and improve customer experiences. I’m proficient in Python, PySpark, SQL, and cloud platforms (AWS, Azure, GCP), with a strong focus on MLOps, CI/CD, Docker/Kubernetes, and model observability with MLflow. I’m passionate about responsible AI, NLP, GenAI, A/B testing, and time-series forecasting, and I strive to deliver compliant, scalable AI solutions that align with business goals. In my recent roles at Centene Health and HCL Tech, I’ve designed end-to-end MLOps pipelines, led multi-agent RAG copilots, and driven measurable impact—from faster fraud detection and improved accuracy to cost savings and regulatory automation. I enjoy collaborating with cross-functional teams to turn complex data into practical business outcomes while upholding governance and fairness in AI systems.…Hi, I’m Meghana Reddy Manda. I’m a results-driven AI/ML Engineer with 4+ years of experience architecting and deploying production-scale machine learning and generative AI solutions across finance, healthcare, and enterprise domains. I specialize in building LLM-powered applications, RAG pipelines, fraud detection, and personalization systems that boost efficiency, reduce costs, and improve customer experiences. I’m proficient in Python, PySpark, SQL, and cloud platforms (AWS, Azure, GCP), with a strong focus on MLOps, CI/CD, Docker/Kubernetes, and model observability with MLflow. I’m passionate about responsible AI, NLP, GenAI, A/B testing, and time-series forecasting, and I strive to deliver compliant, scalable AI solutions that align with business goals. In my recent roles at Centene Health and HCL Tech, I’ve designed end-to-end MLOps pipelines, led multi-agent RAG copilots, and driven measurable impact—from faster fraud detection and improved accuracy to cost savings and regulatory automation. I enjoy collaborating with cross-functional teams to turn complex data into practical business outcomes while upholding governance and fairness in AI systems.

Meghana Reddy Manda

Data Scientist, AI Engineer, AI Developer, +6

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Hi, I’m Meghana Reddy Manda. I’m a results-driven AI/ML Engineer with 4+ years of experience architecting and deploying production-scale machine learning and generative AI solutions across finance, healthcare, and enterprise domains. I specialize in building LLM-powered applications, RAG pipelines, fraud detection, and personalization systems that boost efficiency, reduce costs, and improve customer experiences. I’m proficient in Python, PySpark, SQL, and cloud platforms (AWS, Azure, GCP), with a strong focus on MLOps, CI/CD, Docker/Kubernetes, and model observability with MLflow. I’m passionate about responsible AI, NLP, GenAI, A/B testing, and time-series forecasting, and I strive to deliver compliant, scalable AI solutions that align with business goals. In my recent roles at Centene Health and HCL Tech, I’ve designed end-to-end MLOps pipelines, led multi-agent RAG copilots, and driven measurable impact—from faster fraud detection and improved accuracy to cost savings and regulatory automation. I enjoy collaborating with cross-functional teams to turn complex data into practical business outcomes while upholding governance and fairness in AI systems.…Hi, I’m Meghana Reddy Manda. I’m a results-driven AI/ML Engineer with 4+ years of experience architecting and deploying production-scale machine learning and generative AI solutions across finance, healthcare, and enterprise domains. I specialize in building LLM-powered applications, RAG pipelines, fraud detection, and personalization systems that boost efficiency, reduce costs, and improve customer experiences. I’m proficient in Python, PySpark, SQL, and cloud platforms (AWS, Azure, GCP), with a strong focus on MLOps, CI/CD, Docker/Kubernetes, and model observability with MLflow. I’m passionate about responsible AI, NLP, GenAI, A/B testing, and time-series forecasting, and I strive to deliver compliant, scalable AI solutions that align with business goals. In my recent roles at Centene Health and HCL Tech, I’ve designed end-to-end MLOps pipelines, led multi-agent RAG copilots, and driven measurable impact—from faster fraud detection and improved accuracy to cost savings and regulatory automation. I enjoy collaborating with cross-functional teams to turn complex data into practical business outcomes while upholding governance and fairness in AI systems.

Available to hire

Hi, I’m Meghana Reddy Manda. I’m a results-driven AI/ML Engineer with 4+ years of experience architecting and deploying production-scale machine learning and generative AI solutions across finance, healthcare, and enterprise domains. I specialize in building LLM-powered applications, RAG pipelines, fraud detection, and personalization systems that boost efficiency, reduce costs, and improve customer experiences. I’m proficient in Python, PySpark, SQL, and cloud platforms (AWS, Azure, GCP), with a strong focus on MLOps, CI/CD, Docker/Kubernetes, and model observability with MLflow. I’m passionate about responsible AI, NLP, GenAI, A/B testing, and time-series forecasting, and I strive to deliver compliant, scalable AI solutions that align with business goals.

In my recent roles at Centene Health and HCL Tech, I’ve designed end-to-end MLOps pipelines, led multi-agent RAG copilots, and driven measurable impact—from faster fraud detection and improved accuracy to cost savings and regulatory automation. I enjoy collaborating with cross-functional teams to turn complex data into practical business outcomes while upholding governance and fairness in AI systems.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

English

Fluent

Work Experience

AI/ML Engineer at Centene Health

August 1, 2024 - November 7, 2025

Developed and productionized a multimodal AI pipeline integrating text and tabular data using Hugging Face Transformers, PyTorch, and AWS SageMaker, improving model interpretability and decision confidence by 22%. Architected LLM-powered agentic systems with LangChain, LangGraph, and CrewAI, enabling inter-agent memory and collaboration, improving workflow task completion by 30% across multiple financial operations. Fine-tuned LLMs for clinical and legal summarization tasks, enhancing accuracy by 27% and reducing analyst review workload by 15 hours weekly. Built a real-time fraud detection pipeline using XGBoost, PySpark, and SageMaker, achieving sub-second predictions, 42% higher detection accuracy, and 30% fewer false positives. Deployed Generative AI solutions using AWS Bedrock (Claude, GPT-4) for document summarization and regulatory filings, achieving 45% faster processing with scalable automation. Optimized AWS SageMaker lifecycle configurations and right-sizing strategies, cutti

ML Engineer at HCL Tech

July 1, 2023 - July 1, 2023

Implemented an end-to-end model governance framework using MLflow, W&B, and Jenkins CI/CD, enabling automated experiment tracking, model versioning, and audit-ready documentation for enterprise AI compliance. Conducted A/B testing of LLM prompts using LangChain and evaluation metrics (BLEU, ROUGE), improving chatbot response accuracy by 18% and customer satisfaction scores. Mentored engineers on LoRA fine-tuning, PEFT, and Responsible AI deployment practices ensuring GDPR and HIPAA compliance across enterprise AI initiatives. Automated ETL pipelines using Python, SQL, and SAS to streamline model ingestion, improving data throughput by 60% and reducing preparation time from days to hours. Developed scalable ML pipelines using PySpark, AWS Glue, and Redshift for real-time analytics, improving data delivery speed and business insights by 60%. Designed XGBoost-based failure prediction models that reduced system downtime by 15% and prevented approximately $1.2M in annual revenue loss. Built

AI/ML Engineer at Centene Health, USA

August 1, 2024 - November 7, 2025

Developed and productionized a multimodal AI pipeline integrating text and tabular data using Hugging Face Transformers, PyTorch, and AWS SageMaker, improving model interpretability and decision confidence by 22%. Architected LLM-powered agentic systems with LangChain, LangGraph, and CrewAI, enabling inter-agent memory and collaboration, improving workflow task completion by 30% across multiple financial operations. Fine-tuned LLMs for clinical and legal summarization tasks, enhancing accuracy by 27% and reducing analyst review workload by 15 hours weekly. Built and deployed a real-time fraud detection pipeline using XGBoost, PySpark, and SageMaker, achieving sub-second predictions, 42% higher detection accuracy, and 30% fewer false positives. Deployed Generative AI solutions using AWS Bedrock (Claude, GPT-4) for document summarization and regulatory filings, achieving 45% faster processing with scalable automation. Optimized AWS SageMaker lifecycle configurations and right-sizing stra

ML Engineer at HCL Tech, India

July 1, 2023 - July 1, 2023