QData - VP of AI (Innovation & Engineering)

The Opportunity: Architecting Intelligence at Sovereign Scale

QData is the Data and AI execution arm for ADQ. We are building the AI Factory that will power the transformation of ADQ s massive portfolio of Operating Companies (OpCos). We are looking for a VP of AI to lead our AI engineering, innovation, and forward-deployed practices.

This is not a theoretical research role. You will sit at the intersection of Innovation (Data Science and Applied AI), AI Engineering, and Forward Deployed Engineering (FDE). Your mandate is to industrialize AI: moving from "vibe-coded" prototypes to resilient, production-grade engines that drive tangible ROI.

You will report to the CTO and collaborate closely with the VP of Data, VP of Solutions & Products, VP of Application Engineering, and VP of Commercials to deliver rapid roll-outs of AI MVPs, solutions, and products.

Role Mission: The Engine of the QData AI Delivery Factory

As the VP of AI, you are the AI visionary and operational leader of the QData AI delivery factory. You will build and lead a high-performance team responsible for architecting core AI engines, agentic workflows, and orchestration layers.

This role requires a unique balance: you must possess the technical depth to mentor Lead AI Engineers on complex RAG pipelines, while having the business acumen to define ROI-driven strategies for OpCo C-suite stakeholders.

Why Join QData?

Impact: You will not just build features; you will transform the economy by deploying AI across critical sectors (Energy, Utilities, Healthcare, Logistics) via the ADQ portfolio.

Scale: Access to massive datasets and the resources of a sovereign wealth fund environment.

Growth: A clear path to C-level leadership in a rapidly expanding organization.

Core Responsibilities

1. Strategy & Executive Leadership (Future CAIO)

Define the technical vision and roadmap for QData s AI capabilities, transitioning us from ad-hoc solutions to a reusable, scalable AI factory platform.

Partner with the VP of Commercials and VP of Solutions & Products to align technical innovation with business outcomes and measurable ROI.

Act as the primary technical voice for AI across the ADQ portfolio, championing "AI Safety by Design" and governance alongside enterprise risk requirements.

1. Leading Innovation & Data Science

Drive the R&D agenda, staying at the bleeding edge of research (e.g., small language models, context window optimization, new embedding techniques) and translating them into practical QData playbooks.

Establish rigorous Evaluation Frameworks (quantitative/qualitative) to measure model performance against business KPIs, ensuring we move beyond "hype" to "value".

1. Mastering AI Engineering & Operations (LLMOps)

Oversee the architecture of robust LLM orchestration layers and high-performance multi-layer memory systems.

Institutionalize LLMOps best practices: automated evaluation (LLM-as-a-judge), monitoring, logging, and versioning for prompts and models.

Ensure the engineering team builds distributed systems that maintain low latency under high throughput.

1. Forward Deployed Engineering (FDE) Management

Lead the FDE practice, ensuring your teams can "get into the trenches" with OpCos to integrate AI into diverse environments-from legacy on-prem stacks to modern cloud infrastructure.

Ensure your team acts as technical partners to the OpCos, navigating technical constraints to deliver MVPs that solve root-cause business problems.

1. Talent & Culture

Recruit, mentor, and retain world-class AI talent, fostering a culture of "Pragmatic Innovation" where engineers choose the effective tool over the theoretical one.

Set the "gold standard" for code quality and engineering rigor across the organization.

Candidate Profile

Experience & Leadership

10+ years of technical experience, with at least 5+ years in leadership roles managing large size AI engineering or data science teams.

Proven track record of deploying AI/ML models in Enterprise or B2B environments, moving beyond notebooks to production-scale applications, incubating and scaling AI Factory.

Experience in a high-growth startup, consultancy, or "Forward Deployed" environment is critical; you must be comfortable leading teams that face customers directly.

Mindset & Behaviors

ROI-Obsessed: You prioritize business impact over research for research's sake.

Bias for Action: You drive your team to ship code and solve problems rather than writing whitepapers.

Low Ego: You are equally comfortable strategizing with the Board or debugging an architectural bottleneck with a junior engineer.

Pragmatic Innovation: You choose the most effective tool for the job-whether a simple script or a complex agentic system

Disclaimer:

This job posting is not open to recruitment agencies. Any candidate profile submitted by a recruitment agency will be considered as being received directly from an applicant. Contango reserves the rights to contact the candidate directly, without incurring any obligations or liabilities for payment of any fees to the recruitment agency.