# Eswar Sai Korrapati

> Software Engineer AI | eSentire

Location: Sunnyvale, California, United States
Profile: https://flows.cv/eswarsaikorrapati

I’m an AI/ML engineer with a strong background in machine learning and deep learning, and I enjoy building systems that make work easier for real teams. I’ve worked across cybersecurity, telecom, and enterprise automation, creating everything from traditional ML pipelines to agentic LLM workflows that run at scale. My experience spans data engineering, model training, evaluation, retrieval, fine-tuning, and cloud deployment.  What drives me is building AI that saves time. I like taking scattered processes and turning them into reliable, intelligent systems. That might be a deep learning model that predicts user behavior, a retrieval pipeline that gives agents the right context, or an autonomous workflow that handles routine tasks without human effort. I’m at my best when I’m fixing problems that slow people down.  I’m moving toward roles where I can bring both sides of my experience together, from ML and DL fundamentals to modern agentic architectures. I want to work on systems that blend reasoning, learning, and automation in a way that feels smooth and predictable. My goal is to help build AI products that fit naturally into everyday workflows and deliver real value for analysts, customers, and business teams.

## Work Experience
### Software Engineer AI @ eSentire
Jan 2025 – Present | Pleasanton, California, United States
Built supervisor-based agent workflows that generate structured JSON for dynamic security dashboards. Designed outputs with data endpoints, UI components, and layouts, enforced strict prompt rules for stability, and used RAG to pull schema and component metadata. Deployed on AWS Lambda with CloudWatch monitoring and partnered with platform teams to harden Kubernetes pipelines.

### Software Engineer AI @ Comcast
Jan 2024 – Jan 2025 | California, United States
Built agentic AI workflows with LangChain/LangGraph using Claude Sonnet 4 to automate support tasks. Added persistent state to multi-agent flows to cut repeated interactions by 30%+, built supervisor–worker patterns to reduce escalations, integrated MCP tools for internal lookups, and shipped to AWS Lambda with CloudWatch and Kubernetes-driven CI/CD.

### Software Engineer @ dentsu
Jan 2020 – Jan 2022 | Hyderabad
Built an XGBoost forecasting model trained on 4.2 million advertising records, improving weekly ROI prediction accuracy by 15 percent and supporting multi-million-dollar budget decisions.
Developed PySpark ETL pipelines processing over 300,000 daily records, cutting feature engineering time by 40 percent and enabling daily retraining.
Deployed real-time inference endpoints on SageMaker with automated scaling, achieving sub-120ms P95 latency and reducing infrastructure costs by 30 percent.
Optimized Flask APIs by restructuring SQLAlchemy queries and adding indexing, improving throughput by 30 percent and reducing report load times from 12 seconds to under eight.
Implemented experiment tracking with DVC to strengthen reproducibility and collaboration across data teams.


## Education
### Master's degree in Computer Science
Montclair State University


## Contact & Social
- LinkedIn: https://linkedin.com/in/eswarsaikorrapati

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Source: https://flows.cv/eswarsaikorrapati
JSON Resume: https://flows.cv/eswarsaikorrapati/resume.json
Last updated: 2026-04-11