Pratyaksh Krishnna
AI-Engineer
Building AI-native products, from prototype to production.
I'm Pratyaksh Krishnna, an AI engineer focused on building intelligent systems that are useful beyond the demo stage.
My work spans RAG, AI agents, multi-agent workflows, backend systems, and full-stack product development.
I work across Python, TypeScript, Node.js, React, PostgreSQL, pgvector, LangChain, and LangGraph.
Open to work: Full-time, freelance, or collabs. Let's talk.
Experience
- S
AI Engineer
CurrentStealth ModeFull-time
Aug 2026 – Present
4 mos · Remote
- H
Software Engineer Intern
HoonartekInternship
Jun 2026 – Jul 2026
2 mos · Remote
- Shipped a natural-language analytics agent on BigQuery Conversational Analytics for logistics client XpressBees, so business users could query profitability and lane performance without writing SQL.
- Built an event-driven ingestion pipeline (GCS → Eventarc → Cloud Run → BigQuery) that auto-loads 6 monthly parquet feeds, with per-file logging and error-folder routing.
- Scoped the agent to 4 purpose-built semantic views and wrote guardrails that block PII exposure, hallucination and out-of-scope answers.
- Enforced IAM role-based access and Cloud Logging across the pipeline, and authored the end-to-end SOP now used by the client’s teams.
GCPBigQueryCloud RunEventarcSQLLLM guardrails
Skills
- LangChain
- LangGraph
- OpenAI
- Claude
- Ollama
- pgvector
- Supabase
- FastAPI
- Celery
- Zod
- Python
- Postman
- Node
- Express
- Bun
- PostgreSQL
- MongoDB
- Redis
- BullMQ
- Kafka
- Socket.IO
- Prisma
- Drizzle
- Docker
- Nginx
- AWS
- GCP
- BigQuery
- TypeScript
- JavaScript
- React
- Next
- Vite
- TanStack
- Tailwind
- shadcn
- SQL
- C/C++
- Rust
- Linux
- Git
- GitHub
- GitHub Actions
Projects
An agentic RAG system that answers questions grounded in both text and images. Multi-query retrieval over vector search, async document ingestion with background workers, web search fallback, and RAGAS-based evaluation to keep hallucinations in check.
A NotebookLM-style research workspace. Organise documents and web pages into workspaces, chat with them through grounded, streaming answers, and turn your sources into study material.
“inside, i'm infinite”