Manager, Field Engineering (AI)

Location: Hybrid in San Mateo or New York, United States; willingness to travel up to approximately 30% for customer engagements and team onsites.

On-target earnings: $270,000–$310,000, plus equity.

Company

hirify.global provides an AI platform for building, training, and serving specialized models across text, image, embedding, audio, and multimodal workloads.

What you will do

• Lead, coach, hire, and develop a distributed team of Field Engineers.
• Own the engagement portfolio across discovery, demonstrations, proofs of concept, and production integrations.
• Lead complex customer evaluations from architecture through production planning and personally support high-stakes technical engagements.
• Build field engineering playbooks, discovery frameworks, POC templates, reference architectures, and reusable technical materials.
• Partner with Sales and revenue leadership on deal quality, pipeline health, forecasting, and territory planning.
• Stay hands-on with POCs, MVPs, load testing, evaluation and fine-tuning pipelines, model serving, and post-sales adoption.

Requirements

• 8+ years of overall experience, including 2+ years managing Field Engineering, Solutions Engineering, Forward Deployed Engineering, or Pre-Sales teams.
• Strong technical foundation in LLM inference, model serving, fine-tuning workflows, and GPU deployment across AWS, Azure, and GCP.
• Demonstrated experience building and shipping production software with enterprise customers.
• Track record of coaching engineers and developing individual contributors into senior and lead roles.
• Strong communication, customer-facing, commercial, and operational skills.
• Experience with enterprise cloud platforms, complex integrations, and production GenAI systems.

Nice to have

• Experience with DPO or RFT fine-tuning workflows.
• Deep familiarity with AI inference, fine-tuning, and the production GenAI ecosystem.

Culture & Benefits

• Flat, small, and talent-dense organization with a strong focus on ownership and impact.
• Opportunity to solve AI infrastructure problems involving low-latency inference and scalable model serving.
• Collaboration with engineers and AI researchers on emerging technologies.
• Inclusive, equal-opportunity workplace that values curiosity, creativity, debate, and shipping code.