Python Developer - Agentic AI Platform

Overview We are hiring a Mid-to-Senior Full Stack Developer to build and extend an Agentic AI platform with strong focus on LLM workflows, orchestration, and backend systems. This role requires a highly independent engineer who can quickly understand existing codebases and deliver production-quality enhancements with minimal guidance. Core Hiring Bar (Non-Negotiable) - Ability to independently read, understand, and modify moderately complex Python modules (~300+ lines) - Comfortable filling knowledge gaps through documentation and reasoning (not dependent on AI-assisted coding tools) - Demonstrated ability to interpret existing systems and implement changes with minimal onboarding Key Responsibilities - Develop and enhance backend services and agentic workflows for the AI platform - Build stateful, multi-step LLM pipelines and orchestration logic - Design, optimize, and maintain retrieval and scoring systems - Debug production issues using logs, traces, and system behavior - Collaborate across teams to deliver scalable and reliable AI-driven solutions - Implement incremental changes with strong testing and validation practices Technical Requirements Python (Senior Level) - Writes clean, idiomatic Python using: - Type hints, dataclasses, Pydantic - Generators and context managers - Strong understanding of: - Async/await and concurrency models - Proficient in Python standard libraries (e.g., pathlib, json, re, collections) - Able to modify existing complex systems independently Backend Development (FastAPI) - Experience building and extending FastAPI services - Strong understanding of: - Request lifecycle - Dependency injection and middleware - Multi-worker deployments and shared state (e.g., Redis) - Able to diagnose issues using logs and traces (minimal debugger reliance) LLM Engineering (Applied) - Experience building production-grade LLM workflows - Strong in: - Deterministic prompt design (structured outputs, low/no temperature) - Handling failure modes (timeouts, malformed outputs) - Understanding of RAG systems: - Chunking, embeddings, similarity scoring Workflow Orchestration (LangGraph or Equivalent) - Experience with stateful orchestration frameworks preferred - Must be able to quickly: - Learn graph/state concepts - Implement multi-step workflows within 1–2 weeks Retrieval & Scoring Systems - Experience with ranking/scoring methods (e.g., BM25, hybrid search) - Ability to tune: - Thresholds, weighting, precision vs recall trade-offs - Capable of building realistic test datasets Diagnostics & Log Processing - Familiar with log ingestion and analysis pipelines - Understands: - Chunking strategies - Pattern extraction vs LLM reasoning - When to use deterministic vs AI-based parsing Infrastructure & Runtime - Hands-on experience with: - Docker / Docker Compose (volumes, dependencies, health checks) - Debugging container runtime issues - Working knowledge of: - Redis (basic operations, TTL, persistence) - Enterprise networking concepts (e.g., proxies) Frontend (Working-Level) - Ability to work with HTML + Vanilla JavaScript - Comfortable with: - DOM manipulation - Fetch APIs and event handling - Able to implement UI changes from requirements (no design dependency) Work Style Expectations - Strong code-first discipline (understands design before coding) - Built-in focus on: - Testing and validation - Log-driven debugging - Writes clean, incremental changes with clear commits - Performs self-review against acceptance criteria - Asks focused, implementation-driven questions Experience & Seniority - Level: Mid to Senior Engineer - Experience: - ~4–8 years in Python development - Proven track record delivering production systems - Experience with LLM-based or AI platforms preferred Ideal Candidate Profile - Highly independent problem-solver - Strong systems thinker (not just feature coder) - Comfortable working in low-AI-assist environment - Bias toward execution, debugging, and delivery quality