Senior Full Stack AI Engineer
Chaos Labs builds technology for safer financial markets, including risk management systems, oracles, and AI models for blockchain protocols and financial institutions. It also develops enterprise AI infrastructure for understanding, governing, and improving organizational AI work.
Funding history
Projects
About Chaos Labs
Chaos Labs provides risk management, oracle, proof-of-reserves, analytics, and AI infrastructure for blockchain protocols, exchanges, institutions, and other financial platforms. Its services include simulation, testing, and analysis tooling for blockchain protocols, as well as price oracles and onchain monitoring that help secure financial markets and digital assets. The company also builds enterprise AI infrastructure focused on visibility into AI workflows, organizational knowledge, governance, and proprietary intelligence.
Skills
About the Role
Own end-to-end development of AI-native products by building responsive frontend applications, scalable backend services and APIs, cloud integrations, databases, testing and CI/CD pipelines, with opportunities to develop AI features involving LLMs, RAG, embeddings, vector databases, and agents.
Requirements
- 5+ years of professional software engineering experience
- Strong Python and JavaScript/TypeScript skills
- Production experience with React
- Backend API and distributed-systems experience
- Familiarity with AWS, Azure, or GCP
- Familiarity with Kubernetes
- Familiarity with SQL and NoSQL databases
- Experience with Rust, Go, or another statically typed language is a plus
- Familiarity with RAG, embeddings, vector databases, AI agents, and prompt evaluation is a plus
- Strong communication, product thinking, and problem-solving skills
- Flexibility to work remotely
- Ability to travel up to 30% of the year
Responsibilities
- Build responsive frontend applications with React and TypeScript
- Develop scalable backend services and APIs using Python and Rust
- Integrate applications with AWS or GCP infrastructure
- Design and maintain databases, integrations, automated tests, and CI/CD pipelines
- Develop AI features involving LLMs, RAG, embeddings, vector databases, and agents
- Monitor and improve application reliability, performance, security, and cost
Benefits
- Equity
- Competitive compensation
- Career growth opportunities
Hiring Process
Hiring Process typically takes two to four weeks, depending on the role: 01/Interview with Talent Lead, 02/Technical Assignment, 03/Interview with Hiring Manager, 04/Interview with CEO.