Shashank Shekhar
Open to EU/Remote
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About

I am a product engineer who thinks in systems: how data moves, how teams operate, and how every decision affects reliability at scale. My work blends product intuition with pragmatic engineering, helping teams move from ambiguity to aligned architecture and delivery.

Over 8+ years, I have built enterprise search platforms, workflow orchestration tools, and AI-integrated automation services. I bring an AI-native mindset with strong guardrails: validation, fallback paths, monitoring, and cost control.

Product Lab

I do not just build portfolio projects. I build real systems around problems I care about: AI, automation, search, and creator workflows.

These start as experiments and evolve into usable products, including the homelab systems I build and document end to end.

Current / Upcoming Products

  • AIVario - AI tool discovery and comparison platform
  • KnowMyLab - Homelab learning and architecture guide
  • Workflow Builder - Visual automation and workflow design tool
  • Catalog AI Assistant - AI-powered product search and filtering system
  • Social Pulse - Social media planning and analytics dashboard
  • Docker Control Panel - Lightweight container management dashboard

Content & Automation Systems

  • Ghost Blog System - Self-hosted publishing platform for long-form content
  • GhostPilot - Automated content engine that generates, schedules, and publishes posts using AI

More products will be added as they move from idea to prototype to real usage.

The goal is simple: build useful systems, ship fast, and evolve them into real products.

System Design & Architecture

  • Event-driven and API-first platform design
  • Multi-tenant data modeling and governance
  • Performance optimization and reliability

Frontend

  • Next.js, Angular, and design system foundations
  • Search UX, workflow builders, data-heavy UI
  • Accessibility-first component architecture

Backend & APIs

  • FastAPI, Node.js, Typesense
  • Workflow orchestration services
  • Schema-driven validation and pipelines

AI & Automation

  • Prompt + schema design for reliable extraction
  • Cost/latency/fallback planning
  • NL to workflow generation

Infrastructure

  • Dockerized services + CI/CD
  • AWS and GCP deployments
  • Observability, logging, and backups

How I work

  • Start with outcomes, map the system, then ship in slices.
  • Keep architecture clean with strong contracts and validation.
  • Use AI responsibly: deterministic paths, logs, and audits.