AI Engineer · Production Systems · Delhi NCR, India
I’m Abhishek. I build the systems behind modern AI products—from inference and evaluation to context engineering and backend architecture—so they remain reliable in production.
10+ years building production software · Serving users in 85+ countries
Independent research · 2026
I ran controlled experiments to understand why code models fail across files, how much navigation context helps, and whether a model’s KV cache can carry that context without adding more tokens.
I enjoy building software that survives real users.
I joined AssessPrep as one of its first engineers in 2016. Over nine years, I moved from frontend to backend, infrastructure, and AI while helping the platform grow to serve users in more than 85 countries.
Today I spend most of my time improving the reliability, latency, and evaluation of production AI systems. I’m particularly interested in context engineering, inference efficiency, and the tooling that helps teams ship AI safely. Outside the day-to-day work, I’m usually testing an inference idea or reading AI systems research.
Production AI · AssessPrep
Developed and deployed fine-tuned models for automated assessment grading and content recommendations, including evaluation, lifecycle monitoring, and the MLOps pipelines needed to update them safely. Also built NLP systems for question analysis and an in-house RAG support bot.
Infrastructure · AssessPrep
Helped scale the platform to serve users in 85+ countries. Moved a monolith to Kubernetes-based services, automated delivery with Terraform and CI/CD, and introduced monitoring and autoscaling. Deployment time fell 70%, infrastructure cost fell 40%, and reliability reached 99.9%.
Working with Go · Python · Node.js · Kubernetes · Terraform · AWS/GCP
Good AI products are reliable before they’re clever, measured before they’re optimized, and useful before they’re impressive.
Code models often fail because they don’t know what exists elsewhere in the repository. I tested how file paths, symbols, full-file context, and KV cache reuse change that.
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