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Hi, I’m Sujith Kreddy, a Generative AI and machine learning engineer with 9+ years of experience delivering production-grade AI and data-driven solutions across healthcare, financial services, insurance, and retail. I design scalable AI systems that turn domain-specific content into grounded insights and practical tools for product teams and customers. I enjoy collaborating with product managers, data scientists, and domain experts to translate business problems into reliable ML platforms, CI/CD pipelines, and governance-ready deployments. I’m passionate about performance, responsible AI, and continuous experimentation to drive measurable improvements in customer engagement and operational efficiency.…Hi, I’m Sujith Kreddy, a Generative AI and machine learning engineer with 9+ years of experience delivering production-grade AI and data-driven solutions across healthcare, financial services, insurance, and retail. I design scalable AI systems that turn domain-specific content into grounded insights and practical tools for product teams and customers. I enjoy collaborating with product managers, data scientists, and domain experts to translate business problems into reliable ML platforms, CI/CD pipelines, and governance-ready deployments. I’m passionate about performance, responsible AI, and continuous experimentation to drive measurable improvements in customer engagement and operational efficiency.

Sujith Kreddy

AI Engineer, Data Scientist, Full Stack Developer, +1

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Hi, I’m Sujith Kreddy, a Generative AI and machine learning engineer with 9+ years of experience delivering production-grade AI and data-driven solutions across healthcare, financial services, insurance, and retail. I design scalable AI systems that turn domain-specific content into grounded insights and practical tools for product teams and customers. I enjoy collaborating with product managers, data scientists, and domain experts to translate business problems into reliable ML platforms, CI/CD pipelines, and governance-ready deployments. I’m passionate about performance, responsible AI, and continuous experimentation to drive measurable improvements in customer engagement and operational efficiency.…Hi, I’m Sujith Kreddy, a Generative AI and machine learning engineer with 9+ years of experience delivering production-grade AI and data-driven solutions across healthcare, financial services, insurance, and retail. I design scalable AI systems that turn domain-specific content into grounded insights and practical tools for product teams and customers. I enjoy collaborating with product managers, data scientists, and domain experts to translate business problems into reliable ML platforms, CI/CD pipelines, and governance-ready deployments. I’m passionate about performance, responsible AI, and continuous experimentation to drive measurable improvements in customer engagement and operational efficiency.

Available to hire

Hi, I’m Sujith Kreddy, a Generative AI and machine learning engineer with 9+ years of experience delivering production-grade AI and data-driven solutions across healthcare, financial services, insurance, and retail. I design scalable AI systems that turn domain-specific content into grounded insights and practical tools for product teams and customers.

I enjoy collaborating with product managers, data scientists, and domain experts to translate business problems into reliable ML platforms, CI/CD pipelines, and governance-ready deployments. I’m passionate about performance, responsible AI, and continuous experimentation to drive measurable improvements in customer engagement and operational efficiency.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Gen AI Engineer at McKesson

June 2, 2024 - Present

Led the development of a Gen AI-powered clinical knowledge assistant on Microsoft Azure, enabling semantic search, summarization, and retrieval of contextual answers from large enterprise drug and clinical document collections. Designed end-to-end Retrieval-Augmented Generation (RAG) pipelines using Azure OpenAI, Azure AI Search, and Azure Blob Storage to generate grounded, cited responses. Built and deployed containerized ML services with Python, FastAPI, Docker/Kubernetes, and CI/CD for cloud-native environments, supporting real-time and batch inference with monitoring and governance. Implemented LangChain-driven LLMS workflows with multi-turn conversations, context retention, auto tool invocation, and source attribution. Optimized performance through intelligent caching, context management, and scalable orchestration.

AI/ML Engineer at New York Life

October 1, 2022 - May 1, 2024

Developed production-grade ML and AI solutions to enhance customer engagement and cross-sell opportunities. Built scalable data ingestion pipelines moving structured/transactional data into cloud data lakes and orchestrated end-to-end ML workflows. Performed exploratory data analysis, feature engineering, and model training (recommendation systems, credit risk metrics) using Python, Pandas, NumPy, Spark, and ML frameworks. Implemented A/B tests, monitoring dashboards, and governance for model deployments with CI/CD and real-time inference.

ML Engineer at Citigroup

May 1, 2019 - September 1, 2022

Designed end-to-end ML analytics for retail and commercial lending portfolios, including predicting probability of default and proactive credit risk mitigation. Built data ingestion pipelines with Cloud Dataflow, BigQuery, and Spark to move large-scale data into analytics platforms; developed feature engineering, model training, and scoring pipelines; and built dashboards to track performance and risk metrics. Implemented model validation, cross-validation, and governance, collaborating with risk and business stakeholders.

Data Analyst at Azure Solutions

August 1, 2016 - May 1, 2017

Created customer purchase propensity models to identify high-value customers and support targeted marketing campaigns. Built data ingestion and preprocessing pipelines using Python and SQL, cleaned and wrangled large datasets, and developed vector embeddings using embedding models to enable semantic search and grounding. Implemented data dictionaries, lineage, and governance practices to ensure data quality and reproducibility.