Principal AI Engineer (AI)

TL;DR

Principal AI Engineer (AI Enablement Platform): Architecting and building reusable AI platform services and APIs for product teams with an accent on orchestration patterns and evaluation layers. Focus on designing robust multi-step AI workflows, establishing observability patterns, and creating scalable production-ready AI infrastructure.

Location: Remote

Company

hirify.global is a leading technology provider for the fitness industry, focusing on building an AI-native future with agentic experiences and intelligent automation.

What you will do

• Architect and evolve reusable AI platform services and APIs to be adopted across multiple product use cases.
• Design and implement robust orchestration patterns for multi-step AI workflows, including retrieval, tool use, and state management.
• Own the AI evaluation layer by building test harnesses, golden datasets, and quality metrics to ensure reliability.
• Establish observability patterns for AI systems, including tracing, prompt version tracking, and cost visibility.
• Collaborate with Security and Platform teams to embed guardrails, policy controls, and safe defaults into shared services.
• Lead technical design reviews and define reusable standards to create a consistent path for AI development.

Requirements

• Typically 10+ years of software engineering experience, focusing on distributed backend systems and APIs.
• Proven experience taking LLM-powered systems (RAG, semantic search, agent workflows) from prototype to production.
• Deep expertise in backend architecture, system design, API design, and performance optimization.
• Demonstrated ability to define technical standards and influence multiple engineering teams.
• Strong production mindset with experience in observability, reliability, and scalability.
• Excellent cross-functional collaboration skills and learning agility.

Nice to have

• Experience with AI observability and evaluation tools like Langfuse, LangSmith, or Arize.
• Background in building internal developer platforms, SDKs, or shared engineering services.
• Experience with LLMOps practices such as prompt versioning, model routing, and token management.
• Familiarity with AI governance and policy enforcement in production environments.

Culture & Benefits

• Inclusive environment built on respect, trust, and belonging where diverse perspectives drive innovation.
• Strong commitment to professional growth through continuous learning and mentorship.
• Collaborative "One Team" orientation emphasizing mutual support and collective success.
• Opportunity to solve complex, real-world problems using applied AI at a meaningful scale.