Head of Artificial Intelligence

Pagos Consultants; United States; On-site; USD 220,000 - 360,000; Full time

Job summary

Pagos Consultants seeks an AI Leader to own and scale its company-wide AI strategy, reporting to the CEO. You will supervise Data Science, ML, ML Engineering, and AI Engineering teams, shaping the roadmap and driving measurable AI value across products and operations.

You will translate advances in LLMs, agents, and ML into practical business initiatives, establish production-grade AI capabilities, and partner with product, engineering, and GTM to maximize ROI and uptime.

Qualifications

• 10+ years of experience across AI, Machine Learning, Data Science, or closely related technical disciplines.
• Significant experience leading and developing AI, ML, Data Science, or technical engineering teams.
• Proven experience setting technical strategy and delivering large-scale AI or ML initiatives.
• Strong hands-on technical fluency with modern Machine Learning and AI systems.

Responsibilities

• Own and execute the company's AI-native strategy, operating model, and multi-year roadmap.
• Lead and develop teams spanning Data Science, ML, ML Engineering, and AI Engineering.
• Guide production ML, anomaly detection, explainability, and AI governance initiatives.
• Partner with Product, Engineering, GTM, and Operations to turn AI opportunities into product initiatives.

Skills

AI Strategy

Leadership

ML Engineering

Data Science

MLOps

LLMs

Agentic AI

Cloud Infrastructure

Business Acumen

Stakeholder Communication

Education

Bachelor's in CS/Engineering/AI

Tools

ML Frameworks

Cloud Platforms (AWS/GCP/Azure)

LLM Platforms

Job description

A rapidly growing industrial technology company is hiring an AI Leader to own and scale its company-wide AI strategy.

The company provides an AI-powered condition monitoring platform that helps global manufacturers improve equipment reliability, predict failures, and maximize manufacturing uptime.

Its technology combines large-scale sensor and time-series data with machine learning andredictive analytics to generate actionable intelligence around critical industrial assets.

Reporting directly to the CEO, this is a central strategic and technical leadership position spanning Data Science, Machine Learning, AI Engineering, and emerging technologies including LLMs and agentic AI.

The successful candidate will define how AI creates competitive advantage across the business while remaining close enough to the technology to scope initiatives, evaluate technical quality, challenge assumptions, and guide teams through delivery.

What You'll Do

Own the AI Strategy

• Define and execute the company's AI-native strategy, operating model, and multi-year roadmap.
• Identify opportunities for AI to improve customer outcomes, create product differentiation, generate new revenue, and increase operational efficiency.
• Translate emerging developments across LLMs, agents, ML, and the broader AI ecosystem into practical business opportunities.
• Determine where the company should build proprietary capabilities versus leverage external models, platforms, and vendors.
• Establish measurable AI objectives and connect investment decisions to clear ROI.

Lead AI, ML & Data Science

• Lead and develop teams spanning Data Science, Machine Learning, ML Engineering, and AI Engineering.
• Recruit and retain high-performing technical talent as the organization scales.
• Establish technical standards, ownership, accountability, and measurable goals across AI initiatives.
• Remain technically close to the work and provide hands-on guidance where required.
• Create an environment that balances rapid experimentation with production-quality engineering.

Advance Production ML & Applied AI

• Guide the development of ML models that improve reliability intelligence across large-scale industrial and sensor datasets.
• Advance capabilities across anomaly detection, ranking, explainability, alert quality, and physics-based modeling.
• Ensure production ML systems are observable, repeatable, scalable, and operationally reliable.
• Improve MLOps practices across deployment, evaluation, monitoring, and model lifecycle management.
• Lead the development of LLM and agentic AI applications across both customer-facing
• Build a structured process for evaluating and prioritizing AI opportunities across the organization.
• Establish practical guardrails around model usage, AI agents, data access, privacy, security, and acceptable use.
• Define evaluation frameworks for determining whether AI initiatives are creating measurable value.
• Maintain appropriate standards around responsible AI, bias, privacy, and regulatory requirements.

Partner Across the Business

• Work closely with Product and Engineering to turn AI opportunities into clearly scoped product initiatives.
• Partner with GTM, Customer Success, and Operations to identify opportunities for AI to improve customer and employee workflows.
• Collaborate across functions including Finance, HR, Supply Chain, and Customer Support to introduce AI-driven automation.
• Act as the company's senior authority on AI strategy and execution.

Measure & Communicate Impact

• Establish metrics connecting AI investments to revenue, customer outcomes, efficiency, and risk reduction.
• Communicate AI priorities, progress, investment decisions, and tradeoffs to the CEO, board, and senior leadership.
• Evaluate external AI vendors, models, infrastructure, and tooling as the ecosystem evolves.
• Maintain a clear company-wide narrative around where AI can create sustainable competitive advantage.

What We're Looking For

• 10+ years of experience across AI, Machine Learning, Data Science, or closely related technical disciplines.
• Significant experience leading and developing AI, ML, Data Science, or technical engineering teams.
• Proven experience setting technical strategy and delivering large-scale AI or ML initiatives.
• Strong hands-on technical fluency with modern Machine Learning and AI systems.
• Deep understanding of production ML, MLOps, model evaluation, governance, and AI lifecycle management.
• Familiarity with modern LLM architectures, agentic systems, and applied generative AI.
• Experience working with senior executives and translating complex technical concepts into business decisions.
• Strong commercial judgment with the ability to connect technical investment to customer value, revenue, efficiency, and risk.
• Experience operating in fast-moving environments where strategy and technology evolve rapidly.
• Bachelor's degree in Computer Science, Data Science, AI, Engineering, or a related technical discipline.

Particularly Relevant Experience

Experience in one or more of the following areas would be highly valuable:

• Industrial technology or industrial software
• Predictive or preventative maintenance
• Manufacturing technology
• IoT and connected devices
• Condition monitoring
• Sensor-driven products
• Signal processing
• Anomaly detection
• Physics-based modeling
• AWS and cloud infrastructure
• MLOps and ML infrastructure
• Enterprise SaaS integrations

An MSc, PhD, or technology-focused MBA would also be advantageous.

Why Join?

This is an opportunity to take ownership of AI at a rapidly scaling technology company where Machine Learning is closely connected to the core customer proposition.

Rather than operating a standalone innovation function, you'll have the mandate to influence product strategy, engineering, operations, and commercial decision-making while building the technical organization responsible for the next generation of the company's AI capabilities.

You'll work directly with the CEO and senior leadership, with significant autonomy over the AI roadmap, team, technology choices, and how AI is deployed across the organization.