Siva Sahitya Simhadri

WORK HISTORY

EDUCATION

ABOUT SIVA SAHITYA SIMHADRI

I am a Principal AI engineer at New York Life (with 3+ years of experience) where I prototype and develop high-impact Gen - AI solutions that drive business transformation. In this role, I own the end to end development of high - impact AI initiatives, from experimentation to scalable deployment, with a focus on agentic AI pipelines and enterprise-ready generative AI applications. My background combines cutting-edge research and practical industry expertise. I earned my Master’s in Computer Science from Purdue University, where I conducted advanced research in AI/ML and Natural Language Processing. My work has been published in ACM and conferences, earning recognition including a Best Paper Runner-Up Award at Prior to that, I completed my undergraduate degree in Computer Science at NIT Warangal, one of India’s premier engineering institutes.In addition to my research and leadership experience, I am skilled in cloud-native Agentic-AI solutioning, with deep expertise in AWS services for building scalable ML pipelines, deploying enterprise AI applications, and integrating generative AI into business workflows.I am passionate about bridging the gap between AI research and real-world impact, ensuring that AI solutions are not only innovative but also strategically aligned with organizational goals.Core Competencies: • Gen-AI: Architecting agentic AI pipelines, enterprise AI solutions, RAG workflows, fine tuning LLMs with domain specific data. • Research & Publications: ACM, (Best Paper Runner-Up Award) • Cloud & MLOps: AWS services for scalable AI pipelines, model deployment, monitoring (Bedrock, Kendra, AgentCore, EC2) • Full-Stack Engineering: Backend & frontend development, API design, cloud-native applications • Leadership: Leading small teams, mentoring engineers, driving AI strategy and executionTechnical Skills:Programming Languages: C/C++, Java, Python, JavaScript ReactJS, REST API, ASP.NET, jQuery, BootstrapArtificial Intelligence & Machine Learning: • Generative AI (RAG, Agentic Pipelines, LLM Integration) • Machine Learning & Deep Learning (Supervised/Unsupervised, NLP, Computer Vision) • Frameworks & Libraries: PyTorch, TensorFlow, Scikit-learn, LangChain.Cloud & MLOps: • AWS AI/ML Services: SageMaker, Bedrock, Kendra, AgentCore Lambda, S3, DynamoDB, API Gateway, Step Functions • MLOps: Model deployment, monitoring, CI/CD for ML, Data pipelines (ETL, streaming) • Containerization & Orchestration: Docker, Kubernetes, ECS/EKS