AI Engineer

Location: San Francisco, Bay Area, United States; hybrid role

Company

hirify.global is an AI cloud platform company developing open-source and enterprise solutions that combine generative and predictive AI for private-data applications.

What you will do

• Lead end-to-end technical delivery for complex enterprise customer engagements, including workplans, milestones, escalations, and stakeholder relationships.
• Design and build agentic AI systems, multi-agent frameworks, and LLM-powered applications using RAG, fine-tuning, prompt engineering, function calling, and tool use.
• Develop AI applications across the full lifecycle, from problem framing and data exploration through model development, API integration, and production deployment.
• Build scalable backend services, REST APIs, ML pipelines, and LLMOps infrastructure for continuous monitoring and model improvement.
• Integrate AI models into cloud, on-premises, and hybrid customer environments while ensuring performance, stability, and maintainability.
• Coordinate engineers, program managers, and solution architects; review technical outputs, shape architecture decisions, mentor junior engineers, and communicate with customer executives.

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 engagements and coordinating concurrent delivery workstreams.
• Demonstrated 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, and scikit-learn, plus LLM tooling such as LangChain or LlamaIndex.
• Experience deploying AI services in AWS, Azure, GCP, on-premises environments, or Kubernetes.
• Knowledge of prompt engineering, RAG, fine-tuning, RLHF, model evaluation, guardrails, LLMOps, REST APIs, Docker, Kubernetes, and CI/CD.

Nice to have

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

Culture & Benefits

• Remote-friendly and flexible working environment.
• Career growth opportunities.
• Work with a team including Kaggle Grandmasters and experienced machine learning practitioners.
• Focus on responsible AI, inclusion, and AI for Good initiatives.
• Market-leading total rewards.