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AI Engineer with 1+ years in LLM Pipelines & Cloud Infrastructure
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Assessing your cultural and operational fit
AI Backend Engineer with hands-on expertise building production-ready LLM pipelines, semantic vector search integrations, and highly concurrent APIs. Skilled in orchestrating local/cloud models (Ollama, Bedrock), implementing complex rate-limiting systems, and managing cloud infrastructure. Shipped multiple end-to-end AI products, including a sandboxed contract validator and an AST-based vulnerability scanner.
Aligarh Muslim University
Master Of Computer Applications
N/A – June 1, 2025
Validgen (Indie Project)
Solo Founder / AI Backend Engineer
February 1, 2026 – Present
India
Blackcoffer Pvt Ltd
Software Engineer
June 1, 2025 – February 1, 2026
Noida, Uttar Pradesh, India
Frazor Enterprises Solutions
Associate Software Engineer (Internship)
February 1, 2025 – May 1, 2025
Gurgaon, Haryana, India
SEO-Agentica – Multi-Agent Local SEO Auditor
June 24, 2026 – Present
Architected a lightweight, asynchronous multi-agent orchestration engine running fully local LLMs, distributing workloads between gemma3:1b (1.3B) for fast audits and phi4-mini (3.8B) for copywriting to optimize local hardware utilization. Implemented strict schema enforcement leveraging Pydantic v2 validation and Ollama JSON Schema mode, achieving 100% parser compliance and eliminating format errors on generated JSON-LD metadata. Engineered a real-time event-streaming backend using FastAPI Server-Sent Events (SSE) to push agent execution steps to the console, improving perceived UI latency by over 70% compared to standard polling. Developed an interactive React dashboard with Tailwind CSS featuring a side-by-side search preview (Original vs. AI-Optimized) and a validated schema editor to offer immediate SEO feedback.
View ProjectValidex - API Contract Validator
June 24, 2026 – Present
Developed an automated testing platform utilizing FastAPI and pgvector-based RAG pipelines to automatically ingest OpenAPI specs and generate test scripts, reducing manual QA test creation time by 60%. Architected a secure sandboxed environment utilizing Docker to execute generated scripts within isolated containers, mitigating security risks from arbitrary code execution during live testing. Orchestrated async task queuing utilizing Redis to manage continuous test generation, scaling throughput to support 50+ concurrent container tests without memory bottlenecks. Designed a unified contract validation feedback loop that flags breaking changes and automatically increases API test coverage to over 90% across target endpoints.
View ProjectPrepify - AI-Driven Entrance Prep
June 24, 2026 – Present
Built a generative AI assessment pipeline using LlamaIndex to parse study material and auto-generate context-aware MCQs, accelerating mock exam assembly from days to under 5 minutes. Architected a semantic retrieval layer using pgvector within PostgreSQL, optimizing chunk indexing to deliver sub-50ms search latency on vector database lookups. Implemented real-time adaptivity algorithms that adjust test difficulty dynamically based on historical scoring patterns, improving student retrieval accuracy by 25%. Deployed a responsive Next.js frontend with role-based access control (RBAC), securing student score portals and mock-test sessions for over 1,000+ simulated users.
View ProjectLevel 3: GenAI
September 7, 2023 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, including indie projects and contributions to various AI-driven platforms, indicates a proactive and innovative mindset. Their experience with both local and cloud-based LLMs, along with a breadth of technical skills, suggests adaptability and a willingness to explore different solutions. The focus on security, performance, and user privacy aligns well with best practices in software development.
Soft Skills & Operational Fit
The candidate demonstrates strong initiative and problem-solving skills through their solo founder role and personal projects. Their experience in leading migrations and architecting complex systems suggests good operational fit and ability to handle challenging technical tasks. The detailed project descriptions indicate strong communication of technical concepts.