Clera
Founding Engineer
About this role
Join an AI-native fintech startup as a founding engineer to architect autonomous systems that orchestrate complex multi-party financial workflows. You'll own the technical foundation of an intelligent platform that models businesses, reasons about markets, and coordinates financial transactions at scale from day one.
What you'll do
- Build AI systems that model businesses, reconcile conflicting data, and reason about decision propagation across companies and markets
- Design and deploy agents that coordinate extended financial work across hundreds of counterparties while maintaining context and dependencies
- Own end-to-end architecture, evaluations, infrastructure, and product interfaces for complex AI systems
- Help recruit technical teammates and establish engineering standards and operating practices
- Work across backend systems, applied AI, and product layers to convert ambiguous problems into production systems
What they're looking for
- Applied AI and intelligent agent design
- Complex system architecture and infrastructure
- Retrieval systems, memory architectures, and evaluation frameworks
- Full-stack engineering (backend, AI, product)
- Data-intensive systems and processing
- Production system reliability and craftsmanship
- Greenfield or first-principles development
- Financial services domain knowledge
Benefits
- Equity compensation
- Base salary $180,000–$300,000 annually
- On-site in San Francisco
- Founding team opportunity with major technical influence
- Work on cutting-edge AI systems in fintech
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Clera
Clera builds an agentic operating system that automates complex workflows and processes through AI agents, with a platform designed to simplify distributed infrastructure management for developers. The company is hiring Founding Engineers, Customer Engineers, and Product Engineers to develop both backend systems and user-facing interfaces across their AI automation products.
View all jobs at CleraLikely interview questions
- Tell us about a complex, production-grade system you shipped end-to-end. How did you approach architectural decisions and what challenges did you face?
- Describe your experience building intelligent agents or AI systems for business processes. What made them work reliably in production?