Jainam Shah
Software engineer interested in AI systems, developer tools, and turning difficult technical ideas into products people use.
Computer Science graduate from BITS Pilani. Recent work spans AI tooling for databases, large-scale data pipelines, and GPU systems research.
About
I enjoy building software that combines deep engineering with practical impact.
My interests span AI systems, developer tools, infrastructure, and product engineering. I like taking ambitious technical ideas—from research or early prototypes—and turning them into systems that solve real problems carefully.
Outside work you'll usually find me reading, playing badminton or table tennis, or working through a product idea that won't leave me alone.
- Prefer clarity over cleverness.
- Measure what you claim.
- Ship the smallest thing that teaches you something real.
Currently
Full Now page →Working on
Refining how I write about systems and product work—turning internship and research notes into clear case studies. Building this site as a place to think in public.
Learning
Reinforcement learning fundamentals, and how compiler-style optimizations show up in everyday performance work.
Reading
Designing Data-Intensive Applications — slowly, with notes on replication and consistency models.
Thinking about
AI-native software engineering: where models help, where they hide complexity, and how to keep systems inspectable.
Listening to
Instrumental focus playlists while coding; occasional long-form interviews with builders.
Updated 2026-07
Selected work
- Oracle JSON-to-Duality MigratorSchema-only inference with LLMs to migrate documents into relational models without source data.
- Adaptive GPU Power CappingML-guided power caps that save energy and heat with minimal performance cost. Best Poster at HPDC ’25.
- BITS Hostel Allocation PortalILP and hierarchical fairness for ~950 students, with real-time preference collection under load.
- CodeblueEmergency response system for a medical center—web, QR, and WhatsApp triggers with automated escalation.
Questions I'm thinking about
- 01How should AI change the way we design developer tools—without making them opaque?
- 02What does fairness look like when algorithms allocate scarce resources at scale?
- 03Where can systems research become product leverage, not just a paper?
- 04How do we keep correctness first when LLMs enter critical infrastructure?
Connect
If something here resonates—AI systems, engineering, research, or an ambitious product idea—I'd like to hear from you.