Sriraksha Rao

About

Built end-to-end AI features across both fitness and insurance domains, including a full-stack personalized workout recommendation system and a production RAG-based insurance QA assistant at Relevance Labs. Stands out for combining backend/distributed systems skills with practical LLM architecture, evaluation, and risk-aware human-in-the-loop design; notably reduced unnecessary LLM calls by 40% while improving latency and answer reliability.

Key Strengths

• End-to-end ownership of full-stack AI product features
• LLM/RAG system design for insurance QA
• Asynchronous backend architecture with Kafka
• Strong grounding and hallucination-reduction design
• Evaluation and monitoring of AI systems in production
• Performance optimization reducing API latency
• Intent routing that reduced unnecessary LLM calls by 40%
• Human-in-the-loop decision making for high-risk AI use cases
• Ability to operate in ambiguous early-stage environments

Experience

Education

Skills

Languages