Scale AI
Frontier Agents Engineer (Applied AI)
About this role
Scale AI seeks a Frontier Agents Engineer to design, evaluate, and deploy production AI systems that combine large language models with enterprise data, retrieval, and traditional ML. You'll work directly with Fortune 500 customers across industries to build reliable, reasoning-based agents that automate complex workflows while translating cutting-edge AI research into measurable business impact.
What you'll do
- Design and deploy production AI agents leveraging LLMs, reasoning, retrieval, memory, and tool use across diverse customer use cases
- Architect multi-agent systems that coordinate reasoning, planning, tool execution, and human oversight in enterprise environments
- Own the full experimentation lifecycle including hypothesis generation, rigorous evaluation frameworks, A/B testing, and ablation studies
- Translate frontier AI research into production systems by rapidly evaluating new models, prompting techniques, and agent architectures
- Build production-quality systems with emphasis on reliability, observability, latency, safety, and cost optimization
- Partner with enterprise customers to understand business challenges and prototype solutions that evolve into scalable deployments
What they're looking for
- Large Language Models and prompt engineering
- Agent architecture and multi-agent system design
- Retrieval systems and semantic search
- Experimentation and A/B testing methodology
- Production machine learning systems
- Python and software engineering practices
- Enterprise system integration
- Evaluation frameworks and metrics design
Opens the application — the Jobs AI extension fills it for you. Set up autofill
Opens the official application on the employer’s site. No login required.
Scale AI
Scale AI builds a Generative AI Data Engine and ML infrastructure platforms that power LLM training, evaluation, and production serving at scale, along with data solutions for robotics and autonomous driving. The company is hiring Software Engineers for full-stack feature development and infrastructure systems, identity/security specialists for platform engineering, and Solutions Engineers to support enterprise clients and pre-sales processes.
- Website
- scale.com
Likely interview questions
- Describe your experience building or deploying production AI systems. What was the most complex aspect you encountered?
- How would you approach designing an evaluation framework for an AI agent solving an ambiguous customer problem?