BuildingAvailable for research & collaboration
Charu Sneha
Software Engineer · AI Systems Engineer
I build AI systems that ship - agentic architectures, LLM pipelines, and the backend infrastructure behind them.
Currently ExploringAgentic AI systems, RAG pipelines, and LLM systems at production scale
01 / About
Who I am.
What I build.
I'm a Software Engineer who builds AI systems that actually work in production - not just demos. I care about the gap between a model that performs on paper and one that holds up under real load, real users, and real edge cases.
I think in systems. Whether it's an LLM pipeline, an agentic workflow, or a backend API, I'm drawn to how the pieces fit together - and what breaks when they don't. That instinct comes from shipping production code before I ever touched research.
Currently finishing my Master's at Arizona State University (GPA 4.0), where I get to push on harder problems - multi-agent coordination, tool-use, and what it takes to make language models reliable enough to trust.
02 / Experience
Where I've worked.
Jan 2026– Present
Software Engineer (Capstone)
RoundTechSquare
CapstoneRemote
Building an agentic AI chatbot for a project-management dashboard using LLM workflows, MCP architecture, and production backend APIs.
PythonMCPLLMsRAGTool CallingTypeScriptNode.jsFastAPIDocker
2025– 2026
Career Development Assistant
Arizona State University
Part-timeTempe, AZ
Supported student career services and operations, improving engagement and resource accessibility.
2024– 2025
HCI Researcher
Arizona State University
ResearchTempe, AZ
Conducted research on the impact of LLMs on graduate students' cognition, trust, and learning behavior.
PythonLLMsResearch MethodsData Analysis
Dec 2022– Jul 2024
Software Developer - ML Systems
Mr. Cooper (Rocket Mortgage)
Full-timeDallas, TX
Built and productionized ML pipelines processing 3M+ mortgage documents/month, reducing manual verification from weeks to hours while improving underwriting efficiency by 40%+.
PythonPyTorchNLPApache KafkaSQLFastAPIDockerAWS
2022– 2023
Research Assistant - Drowsiness Detection
Anna University (TCE)
ResearchIndia
Developed ML models for real-time driver drowsiness detection using computer vision techniques.
PythonOpenCVCNNsDeep LearningComputer Vision
Jan 2021– Mar 2021
Data Science & Backend Intern
JK Fenner (Siemens Group)
InternshipIndia
Developed data pipelines and dashboards to analyze unstructured data and improve operational efficiency.
PythonPandasPower BIData Analysis
03 / Founder Stack
Ventures.
Building
BuildingSomething's brewing
Upcoming
— to be announced —
Something's brewing
Upcoming
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BuildingBuildingSomething's brewing
Upcoming
— to be announced —
Something's brewing
Upcoming
— to be announced —
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04 / Selected Work
Things I've built.
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04 / Skillset
What I work with.
Programming Languages
- Python
- Go
- TypeScript
- Java
- C++
- SQL
LLMs & Generative AI
- RAG Pipelines
- Fine-tuning (LoRA, QLoRA, PEFT)
- Prompt Engineering
- Transformers (Encoder–Decoder, Decoder-only)
- Vision-Language Models (VLMs)
- Multimodal LLMs (GPT-4V, LLaVA, Gemini)
- CLIP & Contrastive Learning
- vLLM
- Hugging Face
Computer Vision & Image Processing
- OpenCV
- YOLOv8 / Object Detection
- Image Segmentation
- Facial Landmark Detection
- PIL / Pillow
- CNNs (VGG, ResNet, FaceNet)
- Video Stream Processing
AI Agents
- Agentic Architectures (ReAct, Plan-Execute)
- Tool / Function Calling
- Multi-Agent Systems
- Model Context Protocol (MCP)
- Memory-Augmented Agents
- LangChain / LangGraph
Machine Learning
- PyTorch
- Distributed / Multi-GPU Training
- DeepSpeed
- Scikit-learn
- CNNs, RNNs, GANs
- NumPy / Pandas
Backend & APIs
- FastAPI
- Node.js
- REST APIs
- Next.js
- React
- Apache Kafka
Data & Vector Infrastructure
- Embeddings & Semantic Search
- ANN / Vector Search
- ChromaDB / Qdrant / Pinecone
- PostgreSQL
- MySQL
- Redis
Cloud & DevOps
- AWS (EC2, S3, Lambda)
- GCP
- Docker
- Kubernetes
- CI/CD
- Git / GitHub Actions
Systems & Distributed
- Distributed Systems
- Concurrency & Networking
- Batch & Streaming Pipelines
- High-throughput Inference
- System Design
05 / Education
Academic background.
2024 — May 2026ASUGPA 4.0 / 4.0
Master of Science, Software Engineering
Arizona State University
Focus: AI Systems, LLMs, Agentic Architectures
- Capstone: Built an AI-powered chatbot for a project management platform with industry partner RoundTechSquare (SER 517)
- Research: Conducted HCI study on LLM impact on graduate students' cognition, trust, and learning behavior (SER 594)
- Relevant courses: Statistical Machine Learning · Data Mining · Data Processing at Scale · Software Verification & Testing · Programming Languages & Paradigms · Advanced Data Structures & Algorithms · Foundations of Software Engineering · Software Project & Quality Management
2019 — 2023TCEGPA 3.82 / 4.0
Bachelor of Engineering, Computer Science
Anna University (TCE)
Focus: Software Engineering, Data Systems
- Strong foundation in algorithms, data structures, and systems programming
06 / Publications
Research work.
2026
Adopting AutoML, Graph Data Analytics, Industrial Internet of Things for Traumatic Injury Diagnosis and Treatment
M. Nirmala Devi, B. Subbulakshmi, S. Sridevi, Charu Sneha Laguduva Ravi
Thiagarajar College of Engineering (Under Review)
Proposes an AI-driven framework integrating AutoML, Graph Data Analytics (Neo4j), and IIoT for traumatic injury diagnosis. Combines YOLOv8-based abdominal CT scan analysis with LLM-powered knowledge graphs and chatbot interfaces for real-time disease prediction and clinical decision support.
2025
Impact of LLM Tool Use on Graduate Students' Cognition, Trust, and Learning Behavior
Charu Sneha Laguduva Ravi
Arizona State University — HCI Research
Investigated how LLM tool use affects student reasoning, trust calibration, and learning outcomes through behavioral studies and survey data analysis. Surfaced patterns in LLM-assisted vs. unassisted learning and contributed findings toward responsible AI integration in educational settings.
2023
Real-Time Driver Drowsiness Detection Using Ensemble Deep Learning
Charu Sneha Laguduva Ravi
Anna University — Thiagarajar College of Engineering
Developed a real-time driver drowsiness detection system using an ensemble of deep learning models - VGG, FaceNet, and ResNet - for eye state classification and facial landmark analysis. Built an OpenCV video processing pipeline for frame extraction and evaluated model robustness across varying lighting conditions and head pose variations.
07 / Connect
Let's build
something.
I'm always open to research collaborations, interesting engineering problems, or just a good conversation about AI. Reach out — I read everything.