Ai Engineer Jobs

About The Position

Requirements

• 8+ Years of Systems Expertise: You are a seasoned engineer who is highly comfortable navigating massive, complex codebases and delivering production-grade, distributed software.
• Production AI Experience: You have a proven track record of moving AI beyond prototypes. You possess a deep understanding of prompt engineering, fine-tuning, RAG architectures, and orchestrating multi-agent workflows.
• Developer-First Mindset: You are passionate about Developer Experience and Productivity. You intuitively understand what makes an internal tool frictionless, fast, and empowering for other engineers.
• Strategic Execution: You don't just build wrappers; you think deeply about data privacy, security, cost management, and systemic reliability when deploying AI solutions.
• Exceptional Communication: You can seamlessly translate bleeding-edge AI capabilities into clear, actionable infrastructure strategies, mentoring junior engineers and aligning cross-functional stakeholders along the way.
• Working as a Team: You work across team boundaries and bring other teams and groups along with you towards our strategic vision.

Responsibilities

• Architect AI Core Infrastructure: Design, scale, and maintain the internal platform and APIs that integrate LLMs into the developer workflow, with a heavy focus on autonomous agents, custom retrieval-augmented generation (RAG), and smart context-delivery systems.
• Drive Technical Leadership & Vision: Establish engineering best practices for building with AI at Gusto, including robust evaluation frameworks (evals), guardrails for code safety, and strategies for optimizing model latency and token spend.
• Collaborate & Evangelize: Partner closely with product engineering teams to uncover systemic friction points, and collaborate with core Infrastructure and Security teams to ensure all AI tooling is scalable, compliant, and secure.
• Optimize Feedback Loops: Identify and eliminate critical bottlenecks in the local-to-production lifecycle at scale across Gusto.
• Maintain Enterprise Reliability: Treat AI infrastructure with production-grade rigor. Monitor system health, diagnose complex integration or networking issues, and mitigate model drift or downtime.

Benefits

• competitive base pay
• benefits
• equity (RSUs)