Background and operating style
About
I started in enterprise backend engineering and gradually moved toward AI systems because the hardest product problems kept living at that boundary: search, automation, observability, recovery, and trustworthy autonomy.
Today I care most about building systems that are ambitious without being reckless. That usually means rigorous fallbacks, measurable quality, explicit state, and tooling that helps teams move faster without creating hidden fragility.
Education
Bangalore Institute of Technology
Bachelor of Engineering, Computer Science
2018 - 2022
CGPA: 7.2
What I value
Reliability over theater
I prefer proof, observability, and recovery plans over flashy claims. The interesting part of AI work starts after the demo succeeds once.
Context before code
I like understanding the product, deployment environment, and failure surface before I decide what architecture is justified.
Depth that compounds
I intentionally go deep on a few areas that reinforce each other: backend systems, AI reliability, search, and automation workflows.
Technical skills
Languages
AI and ML
Backend
DevOps and data
Certifications
- Neural Networks and Deep Learning - deeplearning.ai
- Improving Deep Neural Networks - deeplearning.ai
- Introduction to subagents by Anthropic
- Apache Kafka - IBM
- Enterprise Design Thinking - IBM
Let's connect
Open to opportunities
I'm looking for roles at the intersection of AI systems, backend engineering, and reliability.
Outside work
- I mentor and advise through Topmate when I can be concrete and useful.
- I write occasionally on Medium, usually when I have something implementation-heavy worth documenting.
- A lot of my personal time currently goes into multilingual NLP, agent systems, and AI security-oriented builds.
Find me online