Priyank Agrawal
Back End Developer @Planet Sustech
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WORK HISTORY
Back End Developer @Planet Sustech
Architected ESG Analytics Chatbot using LangChain and Groq LLaMA 3.3—a RAG-based conversational assistant that converts natural language queries to MongoDB aggregation pipelines with 95%+ accuracy, reducing manual data analysis time by 70%• Built multi-agent LLM system with intent routing, dynamic prompt engineering, and context-aware responses, enabling sustainability analysts to query emissions data naturally across 500+ organizations• Developed BRSR reporting platform with automated document generation (PDF, Word, XML/XBRL), processing multi-facility sustainability data with export capabilities for regulatory compliance• Engineered Supplier Engagement Portal for Scope 3 emissions tracking with automated assessment workflows, enabling organizations to engage suppliers and collect emissions data through dedicated portal• Optimized backend performance achieving 50% reduction in API response times through strategic MongoDB indexing and aggregation pipeline optimization, while implementing Redis Pub/Sub for real-time notifications• Integrated AWS SES for automated email workflows and built event-driven architecture supporting real-time data synchronization across distributed systems
EDUCATION
IPS College of Technology & Management, Shivpuri Link Road, Gwalior
Bachelor of Technology - BTech, Computer Science and engineering
Well founded higher secondary school
Higher Secondary
Well Founded higher secondary school
High School
ABOUT PRIYANK AGRAWAL
As a Software Developer with 2.5+ years specializing in AI/LLM applications, I architect production-grade systems using LangChain, Groq LLaMA 3.3, and RAG. I\'ve built chatbots achieving 95%+ accuracy in query understanding, designed agentic workflows that reduced manual work by 70%, and created distributed systems handling real-time data processing at scale.Recent AI/LLM Projects:→ Built ESG Analytics Chatbot using RAG—converts natural language to MongoDB aggregations with 95%+ accuracy→ Architected multi-agent LLM system with intent routing and context management, reducing analyst workload by 70%→ Developing NextRole—7-agent career copilot with SSE streaming and NLP-powered semantic search→ Created BRSR reporting platform with automated PDF/Word/XML generation serving 500+ organizationsAI/LLM Stack:LangChain, Groq (LLaMA 3.3), RAG, Prompt Engineering, Multi-Agent Systems, NLP, Intent Classification, Semantic SearchBackend & Infrastructure:Node.js, Express.js, NestJS, FastAPI, MongoDB, PostgreSQL, Redis (Pub/Sub), AWS (Lambda, EC2, Cognito, SES), Socket.IO, DockerCurrently exploring:Agentic AI architectures, LangGraph, LLMOps, advanced prompt engineering, multi-agent orchestration, and vector databases Resume: https://drive.google.com/file/d/1B_aA5tbJvBO6045N7EFK7s79o8XIw1NA/view?usp=sharing
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