Senior Staff Frontier Agents Engineer (AI)

TL;DR

Senior Staff Frontier Agents Engineer (AI): Building and deploying production-grade AI agents and multi-agent systems for enterprise customers with an accent on customer integrations, data pipelines, RAG architectures, and model evaluation. Focus on architecting secure AI workflows, optimizing prompts, debugging complex systems, and translating recurring customer needs into scalable product improvements.

Location: San Francisco, New York, or Seattle, United States

Salary: $288,000–$360,000 USD base salary, plus equity and benefits.

Company

Scale AI develops data annotation, generative AI, and enterprise AI solutions that help organizations build and deploy reliable production AI applications.

What you will do

• Partner with enterprise customers to understand infrastructure, data pipelines, security requirements, and business use cases.
• Design and implement integrations with cloud platforms, data warehouses, internal APIs, and customer-managed environments.
• Build production AI agents, multi-agent architectures, RAG systems, evaluation frameworks, and human-in-the-loop workflows.
• Develop prompt libraries, run experiments and A/B tests, and optimize model outputs for customer-specific domains.
• Act as the primary technical contact for strategic accounts, provide enablement, and collaborate with customer engineering teams.
• Prototype solutions, debug issues across the stack, and identify opportunities to turn common customer patterns into product improvements.

Requirements

• 12+ years of software engineering experience with strong data structures, algorithms, and system design fundamentals.
• Production Python expertise and experience with modern AI/ML frameworks such as LangChain, LlamaIndex, Hugging Face, or the OpenAI API.
• Experience with AWS, GCP, or Azure and modern data infrastructure.
• Strong problem-solving skills and the ability to iterate rapidly through ambiguous requirements.
• Excellent communication skills for explaining complex technical concepts to technical and non-technical audiences.
• Ability to work in the listed United States locations.

Nice to have

• Experience deploying AI agents or autonomous systems, including LLM prompting, embeddings, RAG, vector databases, or semantic search.
• Experience with Docker, Kubernetes, CI/CD, Terraform, Bicep, or other infrastructure-as-code tools.
• Background in DevOps, platform engineering, infrastructure, enterprise security, compliance, or governance.
• Experience in technical consulting, solutions engineering, product engineering, customer enablement, or teaching.
• Open-source AI/ML contributions or expertise in finance, healthcare, government, or manufacturing.

Culture & Benefits

• Full-time employment with comprehensive health, dental, and vision coverage.
• Retirement benefits, equity compensation for eligible roles, and a learning and development stipend.
• Generous paid time off and a possible commuter stipend.
• Work on enterprise AI applications used across professional services, telecommunications, healthcare, and government.
• Inclusive workplace with equal employment opportunity and reasonable accommodation support.

Hiring process

• Compensation is determined during interviews based on location, skills, experience, qualifications, performance, and education or training.
• The same role may not be reconsidered until 90 days after a previous application evaluation.