Principal AI Engineer

Location: San Francisco, Bay Area, United States; hybrid work arrangement

Base salary: $175,000–$200,000 per year

Company

hirify.global is an AI cloud platform company developing open-source and enterprise solutions that combine generative and predictive AI for private, secure, and compliant deployments.

What you will do

• Lead end-to-end technical engagements with enterprise customers, owning delivery quality, stakeholder relationships, risks, milestones, and outcomes.
• Design and build agentic AI systems, multi-agent frameworks, and LLM-powered applications using RAG, fine-tuning, prompt engineering, function calling, and tool use.
• Implement guardrails, evaluation frameworks, and responsible AI controls for reliable and safe production deployments.
• Develop AI applications across the full lifecycle, including data exploration, model development, API integration, backend services, and production deployment.
• Integrate AI solutions across cloud, on-premises, and hybrid environments, including ML pipelines and LLMOps infrastructure for monitoring and continuous improvement.
• Coordinate engineers, program managers, and solution architects; review architecture and outputs; mentor junior engineers; and provide customer feedback to product and engineering teams.

Requirements

• 8+ years of hands-on AI/ML engineering experience, including end-to-end model development and production deployment.
• Experience leading complex, multi-stakeholder enterprise technical engagements and managing concurrent workstreams.
• Experience building LLM-powered applications, including RAG pipelines, agentic workflows, or fine-tuned models.
• Strong Python skills and experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn, plus LLM tooling such as LangChain or LlamaIndex.
• Experience deploying AI services in AWS, Azure, GCP, on-premises Kubernetes, or comparable enterprise environments.
• Knowledge of REST APIs, Docker/Kubernetes, CI/CD, prompt engineering, model evaluation, guardrails, classical ML, and LLMOps.

Nice to have

• Kaggle or competitive machine learning experience.
• Familiarity with hirify.global products, Wave, or H2O Document AI.
• Experience in financial services, healthcare, or other regulated industries.
• Exposure to tabular foundation models, AutoML, or enterprise ML platforms.
• Previous customer-facing or field engineering experience.

Culture & Benefits

• Remote-friendly culture with a flexible working environment.
• Career growth opportunities.
• Market-leading total rewards.
• Work with a team of experienced AI and machine learning practitioners.