Founder @Napplied | Building Frontier Hiring Workflows Ecosystem | AI Agents & SLM | ex- Software Architect & EM

Bengaluru, Karnataka, India

Bengaluru, Karnataka, India

Bengaluru, Karnataka, India

Bangalore

Bangaon Area, India



Bachelor of Technology - BTech, Electrical, Electronics and Communications Engineering
Jalpaiguri government engineering college
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Software Architect with 10+ years of experience building scalable AI-powered products and turning ideas into production. Passionate about rapid MVP development, agentic AI, and aligning technology with business outcomes. At Draup, I ideated and architected an agentic system that auto-generates industry-grade reports (PPT/PDF) from draup data—bridging analytics and executive insight. Now building Napplied AI - a frontier AI intelligence layer for the future of hiring—an AI-native platform that empowers employers, job seekers, and staffing partners through intelligent hiring workflow orchestration. Powered by talent intelligence, progressive ranking, and a proprietary relevancy framework Also active in academic AI research, co-authoring ESG-focused publications and developing models at the intersection of sustainability and machine learning.
Greater Bengaluru Area
cursor
claudecode
Exclusive Club Member at HSR Founders Club, Nov 2025 - Present · 10 mos, Bengaluru, Karnataka, India, I am part of the Exclusive Club Member in HSR Founders Club DM for business associations and club membership referall
Founder at Napplied, May 2025 - Present · 1 yr 4 mos, Bengaluru, Karnataka, India, Napplied AI We are redefining the HR Tech with a focus on solving the most known problem in Job Relevancy and right org fit jobs and candidates Our Job Search AI Agents understands the job seeker's dilemma to search the right and apply Our Candidate Search AI Agents understands the employer's dilemma for the right fit talents with desired relevancy Morpheus - Context-aware AI Interview Agent(upcoming) to fix the candidate fitment in depth Fillexa- Auto Apply Agent(beta releasing soon) to fix job apply hassles Napplied Research - A deep talent research from the top grade consultants powered by tech and Agentic AI on demand
Software Architect at Draup, Dec 2019 - May 2025 · 5 yrs 6 mos, Bengaluru, Karnataka, India, Managed 4 internal products, including an AI-powered reporting suite, cutting $100–$500/report costs and scaling adoption. Led AI-driven automation, boosting productivity at least 2–3x, saving costs of 100+ researchers, and delivering 10x faster data curation. Managed & scaled the Gateway product, driving 1x → 10x+ growth in data processing speed through re-architecture and optimization. Built high-performance frameworks (pipelines, algorithms, similarity models) processing 10M+ records in few hours with super optimised infra cost & auto-recovery. Scaled engineering org through strategic technical hiring and team leadership. Driven by massive career growth from senior engineer to Software Architect and Engineering Manager and leading cross- functional products at scale within 3 years Tech stack: Deep Architecture, LLM Automations, Agentic AI, Algorithms, Python, Django, Flask, Celery, PostgreSQL, MongoDB
Software Engineer at Versa Networks, Feb 2019 - Dec 2019 · 11 mos, Bangalore, Developed Versa Titan (multi-tier SASE product), enabling one-touch router provisioning with enterprise-grade configurations and advanced network/routing options. Helped mid-market enterprises save thousands in setup costs while simplifying secure branch service deployment. Built and integrated cloud-managed features powered by Versa Operating System (VOS) to deliver scalable, easy-to-deploy SASE with advanced application intelligence. Tech stack: Python, Django, DRF, MongoDB, Gluu (SSO), Kafka, Logstash, Docker, Docker Swarm, MySQL
Senior Software Engineer at PricewaterhouseCoopers - Service Delivery Center (PwC SDC), Apr 2018 - Feb 2019 · 11 mos, Bangaon Area, India, Built an orchestration layer for healthcare ML models, automating subject-data processing for health parameter prediction with zero manual effort. Reduced model tuning cost per subject from $10 → $0.78 (~13x reduction), saving millions at scale with automated tracking & processing. Designed auto-scaling infrastructure to handle growing subject datasets, ensuring performance and cost efficiency. Tech stack: ML model refactoring, Python, Flask, SQLAlchemy, MySQL, GCP, Kubernetes, Pub/Sub, Cloud Storage.
Bachelor of Technology - BTech, Electrical, Electronics and Communications Engineering, Jalpaiguri government engineering college