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Samhith Kakarla
Intern Software Engineer specializing in developer productivity and data/AI systems
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About
Internship experience at Intuit building an LLM-grounded QA system for internal microservice data across 100+ microservices, using a graph database approach (evaluated Neo4j and selected AWS Neptune for production alignment). Also has UC Berkeley research experience (including work with Prof. Dawn Song / Berkeley Eye Research Lab) and cross-functional collaboration with bioinformatics/biology teams to deploy software systems on research servers.
Experience
Education
Key Strengths
- Built an LLM-grounded QA prototype over internal data spanning 100+ microservices
- Pragmatic architecture selection (evaluated Neo4j vs AWS Neptune; chose based on AWS production fit)
- Uses PoC-first approach to validate end-to-end behavior before scaling
- Strong troubleshooting approach for LLM workflows via monitoring/logging and output validation
- Able to identify data-source/grounding issues causing incorrect LLM answers and iterate via model tweaks/fine-tuning
- Adapts technical demos to audience expertise; comfortable with expert-level Q&A
- Cross-disciplinary communicator (worked with biologists/bioinformatics stakeholders to implement needed systems)
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