Savitender Singh
I build scalable backend systems and AI reliability pipelines focused on verification, security, and real-world utility.
Verifiable Reliability First.
I'm a backend and AI systems engineer focused on building infrastructure that makes AI outputs trustworthy, traceable, and production-ready.
My work spans LLM reliability pipelines, healthcare interoperability systems, and scalable API backends, always with an emphasis on architecture first. I specialize in claims verification mechanisms to isolate and prevent LLM hallucinations, ensuring outputs comply with target guidelines.
CURRENTLY: Open to Full Stack / Backend / AI / PD roles · Building verification primitives
youFRHALLUCINATION MITIGATION
"Reliability layer for LLM outputs, claim extraction, verification, and explainability pipeline."
Large language models produce fluent but factually unreliable outputs. Hallucinations, which are confident false claims, make LLMs unsafe for high-stakes domains like healthcare, legal, and financial applications.
Built a multi-stage reliability pipeline that intercepts LLM outputs and extracts atomic factual claims using custom NLP, verifies each claim against trusted knowledge bases, scores confidence weights, and highlights flagged claims.
- Decomposing complex compound sentences into atomic verifiable claims without losing semantic intent.
- Optimizing RAG context lookups to achieve sub-second operational bounds under strict precision checks.
Successfully developed a drop-in interceptor pipeline enabling live fact-checking, auditing, and explainability for LLM applications.
MedFlow
"End-to-end patient referral and resource tracking system for distributed hospital networks."
Independent regional hospitals lack unified stateful patient transfer systems, causing extreme delays, clinical communication failures, and resource bottlenecks during transitions.
Developed an end-to-end patient referral workflow engine connecting hospital nodes, incorporating QR-based lookup grids for bedside patient updates, and real-time dashboard resource syncs.
- Designing schemas supporting isolation rules for multi-tenant clinical logs without cross-contamination.
- Modeling clinical state machines (pending > accepted > closed) to handle transfer conflicts gracefully.
Functional healthcare backend implementing rigorous domain sync constraints and high-speed bedside QR routing.
Internship & Placement Portal
"Full-cycle recruitment backend for institutional placement workflows."
Placement cycles rely on manual coordinating and spreadsheets, introducing data corruption, secure validation failures, and massive delays for job candidates.
Constructed a multi-role recruitment workflow engine incorporating signature-checked JWT authorizations, input sanity validations, and highly optimized database collections.
- Designing multi-tier JWT validations to guarantee robust access isolation between Students, Companies, and Administrators.
- Achieving high write stability during flash registration hours through compound database indices.
Sturdy enterprise-level recruitment router backend featuring production-style validation structures.
Python Developer Intern@Shree Guru Gobind Singh Tricentenary University (SGTU)
- Built backend for an Internship & Placement Portal with focus on scalability and security.
- Developed RESTful APIs for authentication, profiles, resume uploads, and job applications.
- Integrated MongoDB for flexible student data storage and seamless CRUD operations.
- Implemented session-based authentication and validation for secure, reliable access.
Let's build something.
// Available for Full Stack, Backend, AI, and PD positions.