I build systems
that make complex
things feel simple.
Full-stack products, applied AI workflows, and reliable data systems — designed with intent, validated with deterministic code, and built to ship.
Physiological plausibility limits (PLAUSIBILITY_BOUNDS), duplicate detection, and missing unit audits.
SELECTED SYSTEMS
Production-focused applications and systems built around real engineering constraints and verified codebases.
VitalTrace
Personal Health Record Intelligence & Deterministic Data Quality
Full-stack clinical data intelligence system that ingests unstructured lab reports, executes deterministic physiological validation, normalizes test aliases to LOINC standards, and tracks longitudinal biomarkers with zero hallucination tolerance.
- Deterministic biological plausibility limits check (
PLAUSIBILITY_BOUNDS) - PostgreSQL 15+ caller-based RLS via
WITH (security_invoker = true) - Zero-hallucination LOINC dictionary: unmapped tests retain raw names with null codes
DocMind AI
Hybrid RAG Document Intelligence Platform with Page-Level Lineage
Enterprise document question-answering and synthesis engine combining FAISS dense vector search with BM25 sparse keyword matching via Reciprocal Rank Fusion, exact page citation pills, and dual Groq/Ollama inference backends.
WorkWise
Climate-Aware Construction Task Scheduling Engine
Predictive thermal strain and occupational safety platform for Indian construction operations, replacing crude clock rules with Liljegren (2008) physical WBGT modeling, CAQM GRAP regulatory constraint scheduling, and Bedrock AI briefings.
ENGINEERING SKILLS & STACK
Technologies, architectures, and systems verified through shipped codebases and automated test suites.
Languages
7 toolsCore languages used for systems, backend services, and algorithmic problem-solving
Frontend Engineering
5 toolsModern component architectures, state orchestration, and accessible interfaces
Backend & Systems
5 toolsAsynchronous worker queues, REST API design, and distributed architectures
Databases & Storage
6 toolsRelational modeling, vector search indices, and multi-tenant security
AI / Machine Learning
5 toolsApplied NLP, hybrid retrieval pipelines, and sequence modeling
Data Quality & Validation
4 toolsZero-hallucination guardrails, clinical coding standards, and deterministic checks
DevOps & Testing
5 toolsContainerization, automated test suites, and proactive observability
EXPERIENCE & EDUCATION
Verified academic milestones, commercial engineering experience, and competitive algorithmic metrics.
Web Developer @ Satvicpath
Dec 2025 – Mar 2026- Collaborated with stakeholders to gather user requirements and applied sound engineering principles to design and ship responsive, production web applications (React.js, Node.js, HTML/CSS/JS) from feature spec to deployment.
- Built and integrated RESTful APIs to fetch, process, and render real-time data from backend services and databases, improving page load performance and interactivity for end users.
- Integrated Razorpay payment gateway end-to-end, managing secure transaction data flow through backend REST APIs in a cooperative, cross-functional team environment.
Bennett University
CGPA: 7.55 / 10- ▸Rigorous coursework in Data Structures & Algorithms, Object-Oriented Programming, Operating Systems, Computer Networks, and Machine Learning.
- ▸Practical engineering across full-stack applications, distributed async pipelines, and applied AI systems.
- ▸Expected Graduation: June 2027.
Air Force School
75.1%- ▸Science & Mathematics curriculum.
Dr. Virendra Swarup Education Center
80.4%- ▸Foundational STEM and computer science coursework.
FROM INPUT TO INSIGHT
Inspect the 6-stage clinical data quality architecture engineered in VitalTrace.
Deterministic Validator
Executes deterministic biological bounds checks, duplicate specimen collision audits, and missing unit verification. Flags extreme physiological values requiring clinical attention.
Zero unverified AI records: Extreme values cannot bypass human review gate.
// Biological plausibility limits check
export function validateObservation(obs: RawObservation): ValidationResult {
const bounds = PLAUSIBILITY_BOUNDS[obs.loinc_code];
if (bounds && obs.value_numeric !== null) {
if (obs.value_numeric < bounds.min || obs.value_numeric > bounds.max) {
return {
severity: "CRITICAL_PLAUSIBILITY_BREACH",
message: `Value ${obs.value_numeric} outside physiological limits (${bounds.min}-${bounds.max})`
};
}
}
return { severity: "PASS", message: "Valid" };
}HOW I ENGINEER
Four foundational engineering principles applied across full-stack applications, applied AI pipelines, and data systems.
Design the system
Break complex problems into distinct decoupled components, formal schemas, explicit interfaces, and predictable data contracts.
Make data trustworthy
Never allow probabilistic models to become final arbiters. Enforce strict deterministic boundary checks, clinical plausibility limits, and canonical standardization.
Build for reliability
Validate systems with automated test suites, multi-tenant database isolation, explicit error handling, and zero-leakage security boundaries.
Make the result useful
Build interfaces that expose the exact necessary telemetry, preserve source citations, and make the next operational decision immediate.
Have an interesting engineering problem?
I enjoy building useful software, working through complex systems, and turning technical ideas into reliable, well-tested products. Let's connect.