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I am an AI and MLOps Engineer with over 4 years of experience delivering production-ready AI systems supporting thousands of users monthly. I specialize in deploying AI assistants using LangChain and GPT, which have significantly reduced manual support queries and accelerated deployment cycles. My work spans full-stack development, LLM integration, and cloud-native architectures across AWS and Azure. I enjoy collaborating with cross-functional teams to build scalable AI solutions that enhance operational efficiency and user satisfaction. With a strong background in Python, React, and cloud platforms, I am passionate about leveraging AI and machine learning to solve complex business problems and drive innovation.…I am an AI and MLOps Engineer with over 4 years of experience delivering production-ready AI systems supporting thousands of users monthly. I specialize in deploying AI assistants using LangChain and GPT, which have significantly reduced manual support queries and accelerated deployment cycles. My work spans full-stack development, LLM integration, and cloud-native architectures across AWS and Azure. I enjoy collaborating with cross-functional teams to build scalable AI solutions that enhance operational efficiency and user satisfaction. With a strong background in Python, React, and cloud platforms, I am passionate about leveraging AI and machine learning to solve complex business problems and drive innovation.

Abhishek Reddy

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

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I am an AI and MLOps Engineer with over 4 years of experience delivering production-ready AI systems supporting thousands of users monthly. I specialize in deploying AI assistants using LangChain and GPT, which have significantly reduced manual support queries and accelerated deployment cycles. My work spans full-stack development, LLM integration, and cloud-native architectures across AWS and Azure. I enjoy collaborating with cross-functional teams to build scalable AI solutions that enhance operational efficiency and user satisfaction. With a strong background in Python, React, and cloud platforms, I am passionate about leveraging AI and machine learning to solve complex business problems and drive innovation.…I am an AI and MLOps Engineer with over 4 years of experience delivering production-ready AI systems supporting thousands of users monthly. I specialize in deploying AI assistants using LangChain and GPT, which have significantly reduced manual support queries and accelerated deployment cycles. My work spans full-stack development, LLM integration, and cloud-native architectures across AWS and Azure. I enjoy collaborating with cross-functional teams to build scalable AI solutions that enhance operational efficiency and user satisfaction. With a strong background in Python, React, and cloud platforms, I am passionate about leveraging AI and machine learning to solve complex business problems and drive innovation.

Available to hire

I am an AI and MLOps Engineer with over 4 years of experience delivering production-ready AI systems supporting thousands of users monthly. I specialize in deploying AI assistants using LangChain and GPT, which have significantly reduced manual support queries and accelerated deployment cycles. My work spans full-stack development, LLM integration, and cloud-native architectures across AWS and Azure.

I enjoy collaborating with cross-functional teams to build scalable AI solutions that enhance operational efficiency and user satisfaction. With a strong background in Python, React, and cloud platforms, I am passionate about leveraging AI and machine learning to solve complex business problems and drive innovation.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Language

English

Advanced

Hindi

Advanced

Work Experience

AI Assistant Developer at Clogration LLC.

June 1, 2024 - Present

Designed and deployed domain-specific SAP AI agents using LangChain and GPT, reducing employee query resolution time by 40% and improving SAP process efficiency. Built and deployed RAG-based AI agents with Pinecone and ChromaDB to enhance cross-domain information retrieval accuracy by 30% and decrease help desk dependency by 25%. Developed scalable AI agent interfaces using React and FastAPI, accelerating response delivery by 30% and supporting real-time intelligent task execution. Integrated anomaly detection capabilities using Scikit-learn, increasing fraud pattern identification accuracy by 15% and reducing false positives by 20%. Partnered with SAP transformation teams to prototype and deploy reusable AI agents, reducing SAP workflow latency by 40% and improving user satisfaction by 50%.

Full Stack Engineer (Data & MLOps Integration) at Cognizant Technology Solutions

December 31, 2022 - August 1, 2025

Engineered React and Spring Boot microservices for Optum’s platform, accelerating claims processing workflows and boosting intelligent task execution by 60%. Implemented scalable CI/CD pipelines using Docker, Kubernetes, AWS EC2, and PCF blue/green strategies, reducing manual deployment efforts by 40% and system downtime by 30%, while ensuring compliance with privacy-by-design principles in MLOps. Integrated secure authentication workflows using Node.js, JWT, and Hibernate, reducing backend API latency by 70%. Prepared ETL pipelines with Apache Airflow and SQL to process over 1.8PB of healthcare claims data, enabling AI-driven financial insights and cutting reporting cycles by 6 hours. Orchestrated secure deployment of document classification models using SageMaker and FastAPI, achieving 99.9% uptime and reducing inference latency by 20ms.

Software Engineering Intern (Full Stack & MLOps Integration) at Cognizant Technology Solutions

June 1, 2020 - August 1, 2025

Engineered a contract lifecycle management platform leveraging React and Java Spring, accelerating document intake workflows by 30% and enabling task automation via responsive APIs. Integrated AWS S3 for secure contract storage to support scalable, cloud-based document retrieval, enhancing release reliability by 40% through CI/CD pipelines with Docker and Kubernetes. Prepared and cleaned contract metadata for document classification models, improving model accuracy by 80% through effective MLOps preprocessing. Collaborated with cross-functional teams to streamline machine learning-enabled contract approval workflows, increasing system adoption and improving model integration success by 40%.