Full Stack Software Engineer – AI Platform & Applied AI Systems

Chiri builds governed AI systems that operate in the real world, and they are seeking a Full Stack Software Engineer to work on both platform development and applied AI systems. The role involves expanding Chiri Brain’s AI control plane, designing data ingestion pipelines, and developing scraping systems for complex environments.

Responsibilities:

• Build AI control-plane primitives (personas, policies, traceability, execution logs)
• Implement auditable inference pipelines
• Design workflow orchestration for human + agent collaboration
• Develop RAG pipelines with structured retrieval and citation
• Support multi-model execution and evaluation frameworks
• Build secure backend services (Python) and frontend interfaces (TypeScript)
• Design and implement scalable data ingestion pipelines
• Build scraping systems for hard-to-scrape, login-gated, or dynamically rendered sites (e.g., social platforms, marketplaces, auction platforms)
• Handle rate limits, bot mitigation, anti-automation defenses, and data normalization
• Implement image embeddings and similarity search pipelines
• Design scoring or valuation logic that combines multiple data inputs
• Build internal tools that surface AI reasoning transparently for end users
• Work directly with stakeholders to iterate quickly on production systems

Requirements:

• 3–6 years of fullstack engineering experience with production ownership
• Strong Python backend experience (FastAPI, Django, or similar)
• Strong TypeScript frontend experience (React, Vite, or similar)
• Experience building and maintaining scraping systems for complex or protected sites
• Experience designing data pipelines and normalization workflows
• Familiarity with vector databases (PGVector, Pinecone, Weaviate, etc.)
• Experience working with embeddings (text and/or image)
• Comfort building systems that combine AI inference with deterministic business logic
• Strong English communication skills (English C2 for non-native speakers)
• Experience scraping dynamically rendered sites (e.g., heavily client-side JS frameworks)
• Experience working with login-gated or bot-protected environments
• Experience building internal analytics or scoring engines
• Experience designing real-time or near-real-time systems
• Exposure to enterprise governance requirements (RBAC, logging, compliance)