Swanand Kulkarni
Open to work1 years experienceGenAI/Full-Stack Engineer
GenAI/Full-Stack Engineer specializing in Agentic Workflows and RAG pipelines.
Standing Rank
Rank Not Available
Developer Badges
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Skills & Technologies
32 skillsWork Experience
AI Engineer
CyberMeru
- Architected and deployed a multi-tenant, production-grade automated hiring platform from scratch, launched as a featured Maker on Product Hunt and actively utilized by corporate clients for live trials.
- Engineered a scalable multi-tenant vector storage architecture using Weaviate, implementing tenant-based data isolation schema configurations to securely separate client workspaces during concurrent production runs.
- Fine-tuned and trained proprietary Small Language Models (SLMs) specifically optimized for deterministic test evaluation, validation pipelines, and automated system state management.
- Built asynchronous candidate evaluation pipelines using Celery, Redis, and LangChain to orchestrate high-concurrency lifecycle workflows and real-time state-machine updates.
- Implemented resilient session-restoration middleware, dynamic link-expiration rules, JWT authentication schemes, and automated post-interview scoring systems to auto-generate transcripts and diagnostic reports.
- Engineered an enterprise document retrieval ecosystem integrating multi-LLM support (Gemini, Mistral) with LangChain and FAISS vector indices to enable sub-second semantic search over vast corporate data.
- Designed and implemented fine-grained, role-based access controls (RBAC) alongside incremental search mechanics and real-time frontend filtering to guarantee secure text parsing and enterprise safety.
- Configured and maintained the full production ecosystem (Django REST Framework+React) on AWS EC2 clusters using a high-availability infrastructure stack optimized with Gunicorn and NGINX web servers.
Projects
CrawlIQ: Multi-Agent Competitor Intelligence Engine
View Project- Architected an asynchronous, microservice-based multi-agent system structured with a clean separation of concerns across dedicated Scraper, Insights, and Orchestrator layers.
- Engineered a decoupled orchestration layer utilizing async HTTPX service-to-service communication paths to securely ingest raw HTML payloads, structure content models, and pipeline downstream LLM strategic queries.
- Containerized the independent application nodes using Docker and multi-stage builds, managing multi-container execution paths locally via Docker Compose orchestration loops.
- Developed an operational Streamlit MVP interface enabling end-to-end execution of automated web scraping routines and instant delivery of structured strategic competitor product metrics.
Automated RAG Document Extractor Engine
View Project- Built a localized Retrieval-Augmented Generation (RAG) pipeline to securely extract unstructured textual corpora from high-density multi-page PDF documents via PyPDF2 parsing workflows.
- Implemented data chunking optimization routines and integrated Google Generative AI embedding vectors to index parsed semantic nodes within a high-speed, local FAISS vector search database.
- Designed semantic similarity search functions retrieving the top 5 highest-affinity content blocks, contextually injection-pipelining the segments into LLM prompts for deterministic, hallucination-free generation.
Leaderboard Standings
Leaderboard Position Pending
Global test scores, peer standing percentiles, and algorithm leaderboard ranks are updated dynamically.
Assessment Highlights
Assessments Not Completed
Coding evaluations, system assessment results, and conceptual score badges will appear here after taking a test.
AI Collaboration Score
AI Collaboration Score Pending
Developer coding behavior, assistant cooperation, and AI pair-programming indicators are evaluated during live coding sessions.
Role Compatibility Profile
Role Compatibility Analysis Pending
Custom matching reports, candidate role compatibility percentiles, and core engineer strength profiles are processed once conceptual code screenings are complete.
Achievements
Product Hunt Featured Maker
Featured Maker on Product Hunt for MeruBot (AI-Powered Interview Automation SaaS).
Certified Model Context Protocol (MCP) Specialist
Certified Model Context Protocol (MCP) Specialist by Anthropic Academy.
About Details
Professional Bio
GenAI/Full-Stack Engineer with a focus on the Anthropic Claude ecosystem and production-grade Agentic Workflows. Proven track record of architecting live AI systems from scratch, including an automated hiring agent featured on Product Hunt.
Bachelor of Engineering in Computer Engineering
Savitribai Phule Pune University (2021 - 2025)