Clera
Founding AI Engineer
About this role
Join a fast-growing AI-first social platform as a Founding AI Engineer to build core matching and communication systems that power real-world group hangouts for young people. You'll own two mission-critical pillars—social graph matching and multi-channel AI agent workflows—with outsized impact on product direction and technology decisions.
What you'll do
- Design and build AI-driven matching systems using collaborative filtering and graph intelligence to form compatible groups
- Develop social graph infrastructure grounded in real-world interaction data and surface friendship-driving patterns
- Create and iterate on embeddings, ranking systems, and large-scale personalization algorithms
- Design AI agent experiences across messaging channels (Instagram, iMessage, WhatsApp, TikTok) with seamless human-AI interaction
- Orchestrate multi-channel workflows connecting APIs, third-party services, and internal database layers
- Build scalable infrastructure supporting complex, multi-step AI workflows and apply reinforcement learning to real-world outcomes
What they're looking for
- Production ML/AI systems (4–10+ years)
- Collaborative filtering and recommendation systems
- Social graph and personalization algorithms
- Multi-channel messaging APIs and agent frameworks
- Data pipelines and full-stack development
- Embeddings and ranking systems
- Reinforcement learning
- Distributed systems and scalability
Benefits
- Meaningful founding-level equity
- Significant upside in early-stage consumer tech
- Full-time, on-site role in San Francisco with core team
- Autonomy to own problems end-to-end
- Opportunity to shape product direction and technology decisions
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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
- Walk us through your experience building recommendation or matching systems in production—what were the key technical and product challenges you solved?
- How have you approached building AI systems that learn from real-world user behavior and outcomes?