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I take generative AI products from problem statement to production — scoping with stakeholders, shaping the system, and shipping it. My work centres on making generative AI and agent systems accountable: behavioural risk assessment, evaluation harnesses, human-in-the-loop supervision, and explainable multi-agent reasoning. Evidence before prediction. Verification before shipping. |
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MCP-native reliability and evaluation layer for coding agents.
Lets an AI coding agent judge its own deployment readiness through behavioural risk assessment, rollback analysis, and verification planning. Published to npm and the official MCP Registry. |
Open-source human-in-the-loop agent orchestration.
Lifecycle monitoring, mid-run intervention, execution replay, and observability for autonomous coding-agent runs — generalised into reusable orchestration infrastructure. |
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IBM SkillsBuild x BeMyApp AI Builders Challenge, June 2026.
Explainable multi-agent reasoning over controversial refereeing decisions, grounded in the IFAB Laws of the Game. Evidence-backed explanations instead of black-box predictions. Powered by IBM Granite. |
AI-native market intelligence platform.
Full-stack research, analytics, portfolio intelligence, and investment workflows, exposed to agents through the Scrybe Intelligence Protocol (SIP) — an MCP-native programmable interface. |
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Project Intern · Gurugram · Jul 2026 – Present
Recently joined as a Project Intern at NIIT MTS. |
Platforms Management Intern · Remote · Sep 2025 – May 2026
Owned platform modernisation end-to-end: migrated the company web platform off a restrictive site-builder onto a cloud-native stack, shipped Azure Functions, CRM workflows, WhatsApp and email automation, and lead-management pipelines used in daily operations. Improved deployment reliability through monitoring and structured release processes. |
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Startup Catalyst · Remote · Jul 2025
Selected among roughly 20 participants from 600+ applicants. Market research, ecosystem analysis, TAM/SAM/SOM estimation, competitor benchmarking, and product validation across India's early-career hiring ecosystem. |
B.Tech, Computer Science Engineering · 2024 – 2028
GGSIPU, New Delhi. Coursework in data structures, database systems, operating systems, computer networks, and software engineering. |
Coding time — weekly language breakdown from WakaTime
From: 27 July 2026 - To: 03 August 2026
Total Time: 1 hr
Markdown 31 mins >>>>>>>>>>>============== 42.91 %
Text 24 mins >>>>>>>>================= 32.98 %
Other 13 mins >>>>>==================== 18.16 %
Kotlin 3 mins >======================== 04.40 %
PowerShell 1 min ========================= 01.55 %Pac-Man — the contribution graph, played
Isometric year — contributions in 3D
Full metrics dashboard — isocalendar, habits, achievements, notable contributions
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