Vice President of AI Engineering

About the role

Signify Technology is retained on a confidential search for a Vice President of AI Engineering. Our client is past the pilot stage on AI and is now hiring an executive to take it into production properly, with ownership of the strategy, the platform, the spend, and the team. This is a genuine build seat rather than a caretaker one, reporting into the CTO or executive leadership, with a mandate to turn AI investment into shipped product.

Location: Florida (Hybrid or Onsite) preferred. Remote considered nationally for the right leader.

Salary: $240,000 to $310,000 base plus performance bonus (DOE).

Responsibilities

• Own the AI and machine learning engineering strategy and roadmap, and align it to commercial outcomes.
• Build, lead, and grow the AI engineering, machine learning, and MLOps teams, including hiring and mentoring.
• Set the architectural direction for AI systems, including large language model integration, retrieval-augmented generation, and agentic workflows.
• Take AI capabilities from prototype into production, with the evaluation, monitoring, and reliability that requires.
• Own the MLOps and model lifecycle practice, covering deployment, versioning, drift detection, and retraining.
• Own AI infrastructure and compute spend, including model selection, inference cost, and build-versus-buy decisions.
• Establish responsible AI practice, including model governance, evaluation standards, bias review, and data handling.
• Partner with Product, Data, and Security leadership to embed AI into the product and the operating model.
• Evaluate the vendor and model landscape and own those commercial relationships.
• Act as the credible internal and external voice on what AI can and cannot deliver for the business.

Requirements

• 10 or more years in software or machine learning engineering, with 5 or more years leading engineering teams at manager, director, or above.
• Proven ownership of an AI or machine learning strategy and the budget behind it.
• Demonstrated track record of shipping AI or machine learning systems into production at scale, not only proofs of concept.
• Deep, hands-on background in Python and modern machine learning frameworks.
• Strong expertise with large language models, including fine-tuning, retrieval-augmented generation, and evaluation methodology.
• Solid MLOps grounding, including model deployment, monitoring, and lifecycle management.
• Experience deploying AI workloads in AWS, Azure, or GCP, with real awareness of inference economics.
• Track record of building, leading, and retaining an engineering organization.
• Legally authorized to work in the United States.

Benefits

• Competitive base salary plus performance bonus
• Medical, dental, and vision coverage
• 401(k) with employer match
• Paid time off and paid holidays
• Executive ownership of the AI function, its platform, and its budget
• A team you build and lead directly
• A real mandate and real budget, not an innovation-theatre seat