AI-Centric Backend Development
Budget: ₹12,500 – ₹37,500 INR
I’m building a production-grade backend that orchestrates multi-step LLM workflows and serves them through a FastAPI layer. The stack is Python first, so I need someone who is genuinely comfortable with advanced language features, clean architecture, and test-driven habits.
Core scope
• Design and implement LangGraph/LangChain pipelines that call both Claude and OpenAI models.
• Shape a robust PostgreSQL schema from scratch and write the migration scripts to match.
• Expose all functionality via FastAPI endpoints with proper async handling, input validation, and error management.
• Handle PDF generation with ReportLab (or an equivalent you like) for final user-facing reports.
Claude-specific responsibilities
Prompt engineering
Understanding token costs
Caching and optimization
Additional expectations
– Respect token budgets by implementing smart caching and partial responses where sensible.
– Write concise unit tests and lightweight docs so the codebase remains maintainable.
– Keep an eye on performance-to-cost ratios and log usage metrics for later analysis.
Final deliverable is a Git repository containing the fully functioning FastAPI service, migrations, PDF module, and sample tests ready to run with Docker.
Core scope
• Design and implement LangGraph/LangChain pipelines that call both Claude and OpenAI models.
• Shape a robust PostgreSQL schema from scratch and write the migration scripts to match.
• Expose all functionality via FastAPI endpoints with proper async handling, input validation, and error management.
• Handle PDF generation with ReportLab (or an equivalent you like) for final user-facing reports.
Claude-specific responsibilities
Prompt engineering
Understanding token costs
Caching and optimization
Additional expectations
– Respect token budgets by implementing smart caching and partial responses where sensible.
– Write concise unit tests and lightweight docs so the codebase remains maintainable.
– Keep an eye on performance-to-cost ratios and log usage metrics for later analysis.
Final deliverable is a Git repository containing the fully functioning FastAPI service, migrations, PDF module, and sample tests ready to run with Docker.