Full-Stack AI Engineer · GenAI Systems · Product & Automation

I build production-grade AI products — LLM workflows, RAG systems, agent-like automation, and full-stack software with strong ownership and fast iteration.

Portfolio · LinkedIn · Email

I’m a full-stack AI engineer focused on building real-world GenAI systems that deliver measurable impact.

I typically work across:

• LLM workflows & agent systems
• RAG pipelines & retrieval systems
• backend architecture & APIs
• automation systems replacing manual workflows

I prefer owning systems end-to-end: idea → architecture → build → deploy → iterate

• LLM Workflow Orchestration
  Built multi-step pipelines with parallel execution (Temporal)
  → reduced generation time from 20 min → 2 min

• RAG Systems in Production
  pgvector-based retrieval mapping natural language → structured outputs
  → achieved ~99% accuracy in product resolution

• AI Workflow Automation
  WhatsApp-based systems replacing manual processes
  → reduced workflows from 30 min → <1 min

• Self-Healing AI Systems
  Built adaptive testing systems that recover from UI changes automatically

• End-to-End AI Product Ownership
  Designed and shipped full-stack AI products (frontend + backend + infra)

System-level AI writing assistant for macOS

• Works inside any app (no context switching)
• AI rewriting via system-level integration (PyObjC)
• Offline speech-to-text (Whisper)
• Multi-language support

👉 https://github.com/mokbhai/VOX

AI-powered personalized storybook platform

• Parallelized content generation pipeline (text + images + narration)
• 10x speed improvement (20 min → 2 min)
• Temporal-based orchestration
• Payments + fulfillment + multilingual narration

Text-to-test AI platform

• Natural language → executable Playwright tests
• Live browser execution with feedback
• Self-healing selector adaptation
• Built for real-world QA automation

AI + WhatsApp workflow automation

• Reduced process time: 30 min → <1 min
• Self-learning correction system (95%+ accuracy)
• RAG pipeline (pgvector + OpenAI)

Fitness platform with intelligent coaching

• Unified Strava + Garmin data
• Built pace prediction & training logic
• WhatsApp-based engagement system

Languages: Python · TypeScript · SQL · C++
Backend: FastAPI · Node.js · NestJS · Next.js
AI: OpenAI · LangChain · RAG · pgvector · Whisper
Infra: Docker · AWS · Linux · Nginx
Databases: PostgreSQL · MongoDB · Redis
Testing: Playwright · Pytest

• Shipping fast with strong ownership
• Building systems that scale and adapt
• Reducing manual work using AI
• Designing reliable GenAI workflows
• Turning ideas into production systems

Most of my work has been built in fast-paced environments where:

• speed matters
• ownership is expected
• systems must work in production

I’m especially interested in roles where AI + product + engineering intersect.

• Portfolio: https://mokshitjain.jainparichay.in
• LinkedIn: https://linkedin.com/in/mokshit-jain
• GitHub: https://github.com/mokbhai
• Email: mokshitjain18@gmail.com