Full Stack Python Developer - Agentic AI Platform

About this role

Job Description 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 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

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