AI Application Engineer
Recall Labs operates Recall, a tokenized AI skill market for funding, ranking, and discovering AI models and agents.
Maintainer signals as of 9/2/2026
Projects
About Recall Labs
Recall Labs operates a decentralized skill market for AI through the Recall platform. Users can fund valuable AI skills, stake RECALL tokens to curate agents and models, build portfolios, track competition results, and earn rewards when selected agents win. Recall provides AI leaderboards and live arenas covering areas such as cryptocurrency trading, perpetual futures, coding, safety, ethics, empathy, and predictions. It also offers custom arena deployments for organizations seeking to evaluate AI models, agents, products, APIs, or documentation, with deployment, execution, leaderboards, performance charts, and verifiable metrics handled by Recall.
Skills
About the Role
You will translate state-of-the-art AI research into production-ready features, design and run experiments to validate approaches, and ship AI-powered product releases. You will build and maintain experimentation infrastructure, integrate AI tooling into engineering workflows, and optimize model deployment and inference. You will collaborate with engineers and stakeholders to turn research ideas into measurable product improvements and share findings to raise team capability in AI evaluation and context engineering.
Requirements
- Deep familiarity with AI evaluations, reasoning systems, agentic architectures, and context engineering techniques.
- At least 5 years of engineering experience.
- Exceptional programming skills and AI-first workflows.
- Experience with experiment design, A/B testing, and statistical analysis.
- Working knowledge of model deployment, inference optimization, and scaling.
- Proficiency with API integrations across multiple LLM providers, including OpenAI, Anthropic, Google, and open-source models.
- Demonstrated track record of shipping AI-driven product features.
- Experience working in remote, fast-paced, iterative development environments.
Responsibilities
- Identify and prioritize high-potential AI experiments.
- Design and run experiments combining AI evaluations with A/B testing.
- Build and maintain experimentation infrastructure for scalable AI evaluations.
- Translate research into production features and drive product releases.
- Integrate AI tooling into engineering workflows to accelerate adoption.
- Disseminate research findings and build team capability in AI evaluations and context engineering.
Benefits
- Equity
- Competitive benefits
- Fully remote work
- Work with a small passionate team
- Entrepreneurial opportunity with outsized impact
- Contribute to projects at the forefront of the web