Frontier Agents Engineer (Applied AI)

Location: Not specified in the posting.

Salary: $180,000–$225,000 USD annually, with potential equity and benefits.

Company

Scale AI develops data infrastructure and full-stack technologies for building, deploying, and overseeing reliable AI applications for enterprises and governments.

What you will do

• Design and deploy production AI agents using large language models, reasoning, retrieval, memory, tool use, and structured knowledge.
• Build retrieval pipelines, customer intelligence layers, memory systems, knowledge representations, and multi-agent workflows.
• Own experimentation and evaluation using benchmarks, A/B tests, golden datasets, regression suites, LLM-as-a-Judge, and human evaluation.
• Develop reliable production systems with guardrails, fallback strategies, tracing, monitoring, observability, and human-in-the-loop workflows.
• Work directly with enterprise customers to translate ambiguous business problems into AI architectures and scalable production solutions.
• Collaborate with infrastructure and customer engineering teams to deploy AI systems securely in enterprise environments.

Requirements

• 4+ years of experience in software engineering, machine learning, or applied AI.
• Strong Python programming skills and knowledge of machine learning fundamentals and modern language models.
• Experience building production AI systems using LLMs and modern AI tooling such as OpenAI, Claude, MCP, agent frameworks, vector databases, or retrieval systems.
• Experience designing or evaluating AI systems with quantitative metrics.
• Ability to communicate effectively and work directly with enterprise customers.

Nice to have

• Experience with production AI agents, autonomous systems, reasoning, planning, tool use, RAG, semantic search, knowledge graphs, or structured knowledge representations.
• Experience with fine-tuning, distillation, reinforcement learning, small language models, model optimization, or multimodal AI.
• Experience with distributed systems, AWS, Azure, GCP, Docker, Kubernetes, CI/CD, and production observability.
• Experience leading technical workshops, architecture reviews, or customer design sessions.

Culture & Benefits

• Work across applied AI research, forward-deployed engineering, and production enterprise systems.
• Health, dental, and vision coverage.
• Retirement benefits, learning and development stipend, and generous paid time off.
• Potential equity compensation and, for eligible roles, a commuter stipend.
• Inclusive equal-opportunity workplace with reasonable accommodations for applicants with disabilities.

Hiring process

• Compensation is determined during the interview process based on location, skills, experience, qualifications, interview performance, and education or training.
• Applicants must wait 90 days before being reconsidered for the same role.