Full Stack Software Engineer – AI Platform & Applied AI Systems

Location: Remote / South America / Central America

Type: Full-Time

Why Chiri

Chiri builds governed AI systems that operate in the real world — not demos, not prototypes, not black boxes.

Our platform, Chiri Brain, is a governed AI operating system for humans and agents. It ensures AI systems are transparent, auditable, and secure — from prompt to execution.

In addition to our core platform, we design and deploy applied AI systems for clients — AI tools that operate in messy, high-signal, time-sensitive environments.

This role spans both.

Role Overview

We’re hiring a Fullstack Software Engineer to split time between:

• Platform Development (≈60–70%) Expanding Chiri Brain’s governed AI control plane and orchestration systems.

• Applied AI Systems (≈30–40%) Designing and shipping real-world AI systems involving data ingestion, scraping, computer vision, and intelligent scoring workflows.

You’ll work on systems that:

• Ingest messy, real-time external data

• Perform AI-driven classification and similarity detection

• Aggregate multi-source data into structured signals

• Expose traceable AI decisions through production APIs and UIs

This is not a simple LLM integration role. We build systems that must operate reliably under technical, economic, and governance constraints.

Key Responsibilities

Platform Development (≈60–70%)

• 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)

Applied AI Systems (≈30–40%)

• 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

Required Qualifications

• 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)

Preferred Qualifications

• 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)

What We’re Looking For

An engineer who:

• Can move between infrastructure and applied systems

• Understands that scraping in production is a systems problem, not a script

• Thinks in terms of signal extraction, not just data collection

• Can ship fast without sacrificing structure

• Is comfortable building AI systems that must actually make or influence decisions

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