# Goutham Reddy Kasireddy

> Building Applied AI Systems | AI Product Manager & Engineer | LLMs • Agents • Automation • RAG

Location: Houston, Texas, United States
Profile: https://flows.cv/gouthamreddykasireddy

Graduate student in Engineering Data Science at the University of Houston, specializing in applied machine learning, large language models (LLMs), and cloud-native AI systems. I focus on designing and deploying intelligent, scalable solutions across domains such as healthcare, automation, and enterprise productivity.

My technical expertise spans LLM integration (OpenAI, Mistral), generative AI workflows, retrieval-augmented generation (RAG), and multimodal AI. I build and optimize machine learning pipelines using Python, TensorFlow, PyTorch, and Scikit-learn, and manage scalable deployments on AWS and GCP using Docker, Kubernetes, and Terraform.

I’m proficient in prompt engineering, vector databases (Pinecone, FAISS), and frameworks like LangChain and LlamaIndex. I also integrate CI/CD practices and MLOps tools to streamline model deployment and monitoring in production environments.

Recent projects include building neural network models for detecting heart disease using acoustic signals, and developing AI agents capable of automating software tasks through contextual prompting and real-time feedback loops. These projects showcase my ability to translate advanced machine learning concepts into impactful, domain-specific solutions.

I actively follow developments in distributed computing, real-time inference, fine-tuning LLMs, and zero-shot learning. My goal is to push the boundaries of AI application by combining strong theoretical understanding with hands-on engineering.

Always open to collaboration, research, and opportunities where AI can drive measurable outcomes and intelligent automation at scale.

## Work Experience
### AI/ML Engineer @ Bank of America
Jan 2025 – Present | Remote, USA
- Built and deployed churn prediction and CLV models using XGBoost, Ridge/Lasso, and Spark SQL, enabling proactive retention strategies that improved targeting accuracy by ~6% and increased upsell conversion opportunities by 4%.
- Designed and tested an AI-driven recommendation engine on AWS EMR using collaborative and hybrid ML techniques, improving click-through rates by over 7% while reducing low-relevance recommendations during pilot rollout.
- Implemented NLP-powered RAG pipelines with FAISS and LLMs to streamline data validation and reporting workflows, reducing manual effort and improving knowledge retrieval accuracy for Tableau-based executive insights.

### AI Engineer @ PTC
Jan 2023 – Jan 2025 | USA
- Scaled Oplay.ai, a multi-tenant AI automation platform, designing context-aware workflows and prompt orchestration to support diverse enterprise use cases across operations, analytics, and customer experience.
- Integrated and optimized multiple LLMs (OpenAI, Claude, Mixtral) using LangChain and RAG pipelines with Pinecone, reducing inference latency by ~35% while maintaining high response quality and consistency.
- Developed reusable prompt templates, evaluation frameworks, and guardrails to standardize model behavior, improving reliability and performance across multiple AI-driven applications.
- Engineered a high-performance backend using FastAPI, PostgreSQL, and Redis, handling 50K+ daily API requests with sub-200ms latency, while partnering with product and engineering teams to accelerate feature delivery.

### Data Science Analyst @ Bytes Technolab
Jan 2021 – Jan 2023 | India
- Maintained scalable ETL/data pipelines using SQL, Python (Pandas), and PySpark to process and standardize 120K+ daily payment and settlement transactions across multi-region systems, enabling reliable downstream reconciliation and reporting.
- Orchestrated AWS Glue ETL workflows integrating transactional, ledger, and reporting datasets, reducing month-end close cycles by 40% and improving financial reporting efficiency for finance stakeholders.
- Implemented data quality validation and anomaly detection frameworks using SQL to identify duplicate transactions, missing settlements, and revenue leakage, improving data accuracy by 30%+ before executive KPI reporting.
- Performed financial data analysis and forecasting using Advanced Excel (Pivot Tables, Power Query, XLOOKUP, scenario modeling), reducing forecast variance by 15% and enabling more accurate revenue planning and decision-making.


## Education
### Master's degree in Data Science
University of Houston

### B.Tech in Computer Science
Hindustan Institute of Technology and Science

### Intermediate in Junior High/Intermediate/Middle School Education and Teaching
Sri Chaitanya College of Education

### Primary School in 10th Standard
students careers


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

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Source: https://flows.cv/gouthamreddykasireddy
JSON Resume: https://flows.cv/gouthamreddykasireddy/resume.json
Last updated: 2026-04-17