Senior Frontier Agents Engineer (Applied AI)

TL;DR

Senior Frontier Agents Engineer (Applied AI): Designing and deploying production AI agents that leverage LLMs, reasoning, and retrieval to solve complex enterprise workflows with an accent on bridging the gap between cutting-edge AI research and production deployment. Focus on building multi-agent architectures, establishing rigorous evaluation frameworks, and solving high-stakes business challenges.

Location: Likely limited to the United States (based on US Department of Labor compliance, pay transparency provisions, and US-specific benefits).

Company

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications for enterprises and government agencies.

What you will do

• Design and deploy production AI agents using the latest advances in LLMs, reasoning, retrieval, and memory.
• Architect systems that integrate LLMs with structured knowledge, traditional ML, and deterministic software.
• Engineer customer intelligence layers, retrieval pipelines, and memory systems to handle heterogeneous enterprise data.
• Develop multi-agent systems that coordinate planning, tool execution, and human oversight.
• Own the full experimentation lifecycle, from hypothesis generation to production rollout using rigorous evaluation frameworks.
• Partner directly with enterprise customers to translate ambiguous business problems into production AI architectures.

Requirements

• 5+ years of experience in software engineering, machine learning, or applied AI.
• Strong Python programming skills.
• Proven experience building production AI systems using LLMs.
• Proficiency with modern AI tooling, including OpenAI, Claude, MCP, agent frameworks, or vector databases.
• Strong understanding of machine learning fundamentals and modern language models.
• Excellent communication skills for direct engagement with enterprise customers.

Nice to have

• Experience with RAG, semantic search, knowledge graphs, fine-tuning, or reinforcement learning.
• Experience building distributed production systems and working with cloud platforms (AWS, Azure, GCP).
• Proficiency with Docker, Kubernetes, CI/CD, and production observability tools.
• Experience leading technical workshops, architecture reviews, or customer design sessions.

Culture & Benefits

• Comprehensive health, dental, and vision coverage.
• Competitive compensation including base salary and equity grants.
• Retirement benefits and a learning and development stipend.
• Generous PTO and potential commuter stipends.
• Opportunity to work across diverse industries and cutting-edge AI research.