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sawantudayan/README.md

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╔══════════════════════════════════════════════════════════════════╗
║                                                                  ║
║   ❯ whoami                                                       ║
║                                                                  ║
║     Udayan Sawant                                                ║
║     Software Engineer — Data, Feature Infra & ML Platform        ║
║     Wells Fargo · San Francisco, CA                              ║
║                                                                  ║
║   ❯ cat expertise.txt                                            ║
║                                                                  ║
║     LLM fine-tuning · RAG pipelines · LangChain                  ║
║     Vector DBs (Pinecone, Elasticsearch) · Azure · GCP           ║
║     Feature Store · ML Platform · Data Engineering               ║
║                                                                  ║
║   ❯ status --career                                              ║
║                                                                  ║
║     [■■■■■■■■░░]  6+ years in Data & AI                          ║
║     # open to GenAI infrastructure & LLM platform roles          ║
║                                                                  ║
╚══════════════════════════════════════════════════════════════════╝

> ./about --me

I'm a Generative AI & LLM Infrastructure Engineer living at the intersection of data engineering and AI. I don't just train models — I architect the systems around them: the pipelines that feed them, the vector stores that make them smart, the platforms that keep them reliable at scale.

Right now I'm building Feature Infrastructure and the ML Platform at Wells Fargo, shipping production GenAI systems on Azure and GCP. Previously I've built at Netflix, J. P. Morgan, First Republic Bank, and UNICEF — each role a layer deeper into the AI and data stack.

When I'm not wrangling distributed systems, I write on Medium about the system design patterns that actually matter in production.


> cat tech_stack.json

🤖 GenAI / LLM Layer

LangChain HuggingFace OpenAI PyTorch scikit-learn

🗄️ Vector & Search

Pinecone Elasticsearch Weaviate FAISS

⚙️ Data Engineering

Apache Spark Kafka Airflow dbt Databricks Snowflake

☁️ Cloud & MLOps

Azure GCP AWS Kubernetes Docker Terraform

🧰 Languages

Python Java SQL FastAPI


> tail -f /var/log/writing.log

I write about distributed systems, system design patterns, and AI — with the candour most engineering blogs avoid.

[Feb 2025]  CAP Theorem: Why Distributed Systems Force You to Make a Hard Choice
            → https://medium.com/@udayansawant7/cap-theorem-why-distributed-systems-force-you-to-make-a-hard-choice-137567985dae

[Nov 2025]  Security — Federated Identity
            → https://medium.com/@udayansawant7/security-federated-identity-bcbc8ce63b44

[Nov 2025]  Availability — Heartbeats (Part 1 & 2)
            → https://medium.com/@udayansawant7/availability-heartbeats-part-1-996831d42eff

[Nov 2025]  Security — Valet Key
            → https://medium.com/@udayansawant7/security-valet-key-c4b20c865816

[Nov 2025]  Security — Proxy Pattern (The Gatekeeper)
            → https://medium.com/@udayansawant7/security-proxy-pattern-a-k-a-the-gatekeeper-978b3eb60878

[Nov 2024]  How Generative AI is Transforming Work and Life: Beyond the Hype
            → https://medium.com/@udayansawant7/how-generative-ai-is-transforming-work-and-life-a-practical-guide-beyond-the-hype-ffd4c9314991

📖 Read all articles on Medium →


> ping udayan --message "let's talk"

Whether you want to discuss LLM infrastructure, RAG architecture, or just geek out over distributed systems trade-offs — I'm always listening.

Portfolio


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# building AI infrastructure, one pipeline at a time.

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