Chiri · 2 days ago
Full Stack Software Engineer – Governed AI Product Development
United States
Full-time
Remote
Entry, Mid Level
2+ years expChiri is a company that helps teams work smarter by embedding AI into their workflows while ensuring governance and security. They are seeking a Full Stack Software Engineer to build and evolve their governed AI platform, Chiri Brain, focusing on AI governance, workflow orchestration, and auditable data pipelines.
Computer Software
Responsibilities
Build Governed AI Systems: Design and implement core platform features that power Chiri Brain’s AI control plane, including execution tracing, persona enforcement, guardrails, and policy-aware inference
Agent & Workflow Orchestration: Develop orchestration logic for agent workflows—coordinating multi-step tasks, tool usage, and model calls while preserving full auditability and deterministic replay
RAG & Knowledge Systems: Build and evolve RAG pipelines that support shareable document collections, semantic search, metadata extraction, and cited answers—aligned with Chiri Brain’s “see everything” philosophy
Multi-Model AI Control: Implement abstractions that allow workflows to run across multiple models (e.g., OpenAI, Anthropic, local models), including parallel execution and comparison patterns
Backend & Frontend Development: Backend: Python services handling retrieval, orchestration, inference auditing, policy enforcement, and data isolation. Frontend: TypeScript interfaces that expose execution traces, permissions, workflows, and AI interactions in a clear, enterprise-friendly way
End-to-End Ownership: Take features from concept through production—partnering with product, design, and clients to define requirements, scope sprints, and deliver incrementally
Governance-Driven Design: Translate governance requirements (security, compliance, auditability, data retention) into concrete product features rather than after-the-fact controls
Cross-Functional Collaboration: Work closely with stakeholders across HR, Finance, Security, and Engineering to ensure AI workflows align with real operational and regulatory needs
Agile Execution: Use tools like Linear or JIRA to manage work independently, communicate progress, and iterate quickly based on feedback
Qualification
Required
Bachelor's degree in Computer Science, Software Engineering, or a related field
2–4 years of professional full stack engineering experience, with demonstrated ownership of production features
Strong proficiency in: Python (APIs, orchestration logic, data pipelines, AI frameworks like LangChain), TypeScript (React, Vite, or similar modern frontend frameworks)
Hands-on experience with: RAG systems and vector databases (e.g., PGVector, Pinecone), LangChain or similar agent/orchestration frameworks
Familiarity with enterprise AI requirements, including: Audit logging and execution traceability, Privacy-by-design (PII handling, data isolation), Regulatory awareness (GDPR, HIPAA, SOC-style controls)
Comfort using AI-assisted development tools (e.g., Cursor, Claude Code, Codex CLI) to accelerate delivery
Strong English communication skills for documentation, collaboration, and client-facing discussions
Ability to work independently while operating within structured agile workflows
Preferred
Experience building AI platforms, not just AI features
Exposure to agent systems, workflow engines, or orchestration frameworks
Familiarity with RBAC/ABAC, policy engines, or security-conscious backend design
Experience working with enterprise or regulated clients
Benefits
A fast-paced, fully remote environment with meaningful ownership.
The opportunity to help define what 'enterprise-ready AI' actually means.
Access to cutting-edge AI tools, models, and internal playbooks.
The chance to help clients achieve tangible outcomes—like 50% faster workflows—without compromising governance or trust.
Company
Chiri
AI is moving fast—and most teams are fragmented trying to keep up. You’ve seen the demos. You’ve run the pilots.
2-10 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase