Kunal Dhavale
Software Engineer (currently seeking new opportunities)
Integrating Agentic AI and GenAI orchestration into high-scale production insurance workflows.
Intro
I'm Kunal Dhavale, a Software Engineer most recently with Liberty Mutual Insurance, where I specialized in cloud-native backend systems and distributed architectures. My career has been defined by a transition from academic research as a Teaching Assistant to building high-stakes production systems in the insurance industry. I am deeply passionate about the 'boring parts' of AI—the evals, latency, and reliability that actually make GenAI work in the real world—and I've successfully implemented Agentic AI solutions that handle over 10,000 daily requests. I'm currently looking for my next challenge as a Backend Software Engineer, specifically in the Seattle area or remotely. I offer a blend of technical rigor in distributed systems and a pragmatic approach to system design, always aiming to avoid the 'complexity tax' while delivering 99.9% availability.
Networking
What I can offer
- ›Experience shipping high-scale, reliable production systems
- ›Proven track record of GenAI integration into business workflows
- ›Expertise in distributed systems and cloud-native architecture
What I'm looking for
- ›Backend Software Engineer role in the Seattle area or remote
- ›Connections with hiring managers and recruiters in distributed systems and AI/ML
Best fit for
Focus
Current interests
Core competencies
Background
Career
Transitioned from a Graduate Teaching Assistant at the University of South Carolina to a Software Engineer at Liberty Mutual Insurance, specializing in cloud-native backend systems and GenAI.
Education
Master of Science in Computer Science, University of South Carolina (2019 – 2021); Bachelor of Engineering in Computer Engineering, Shivajirao S Jondhale College of Engineering (2015 – 2019).
Achievements
- ›Automated workflows for 10,000+ daily requests using GPT-4 and LangChain.
- ›Designed an aerial risk-scoring pipeline for 1M+ homes using TensorFlow.
- ›Increased processing throughput by 60% using AWS Lambda and MSK.
- ›Reduced document turnaround from days to minutes via DocuSign API integration.
- ›Maintained 99.9%+ availability for financial platforms.
Opinions
- Seniority is defined by pattern recognition and the ability to 'slow a room down' to catch edge cases.
- Advocates for 'modular monoliths' initially to avoid the 'complexity tax' of premature microservices.
- Working in 'boring' regulated industries builds better engineers due to the high stakes and discipline required.
- AWS Lambda is often overused for latency-sensitive or stateful workloads.
Personality
Communication style
Professional, educational, and analytical using a 'Problem-Solution-Insight' structure.
Formality — 7/10
Vocabulary