Founding AI Platform Architect – Autonomous AI Systems (LLMs, RL, Reasoning)

Hudson Modeling has been retained to identify a Founding AI Platform Architect for a new AI venture building systems designed to plan, execute, and optimize real-world business strategies autonomously.

The founder previously served as one of the first Chief Data Science Officers on Wall Street, and later the first Chief AI Officer in private equity, and holds a PhD in AI from Stanford.

Our Client is building AI systems that will advance the field to the next stage of capabilities. These systems do not simply assist humans but embed within the business and execute entire layers of business operations autonomously. Most AI focuses on generating answers or content. We are building a system that can plan actions, run experiments, execute, learn from outcomes, and continuously improve real-world business performance. The goal is to create AI that drives measurable economic results

The platform combines large-scale foundation models, structured reasoning systems, reinforcement learning, probabilistic methods, and search-based approaches to create a new class of AI-native business infrastructure.

This is not another LLM wrapper, nor is not a typical "Head of AI" role.

The Role

We are looking for a technical partner to work directly with the founder to build this core engine from the ground up. This is not a "Head of AI" management role; it is a founding builder position for an engineer who thrives at the boundary of frontier research (RL, MCTS, Probabilistic Logic) and production-grade systems. You will define the architecture that allows foundation models to interact with complex business environments, ensuring our systems don't just "reason", they deliver.

You will be a strong fit if you have experience with some, or several of the following:

• LLM-based systems and advanced agent architectures
• Reinforcement learning and feedback-driven optimization
• Reasoning systems and planning techniques (e.g. MCTS)
• RAG pipelines and knowledge integration
• Evaluation frameworks for generative systems
• Scalable ML infrastructure and experimentation environments
• Designing AI systems that operate under real-world constraints

We are particularly interested in Staff / Principal-level AI Engineers, early AI startup builders, or technical leaders who still enjoy building hands-on.

Compensation - Salary will be market reflective and based on location and experience. There's also Bonus / Stock available.

Why this role is unique:

• Foundational ownership of a new AI platform
• Clean technical canvas with significant architectural influence
• Opportunity to translate frontier AI techniques into real economic impact
• Work directly with a highly experienced AI founder and early team

Additional Signals We Value

Because this is a founding-stage role working closely with the CEO on both system architecture and the long-term platform narrative, we are particularly interested in candidates who have operated in environments where technical direction and company building are closely connected.

Strong candidates may have experience such as:

• Early engineering roles in venture-backed startups
• Work within frontier AI organisations
• Recognised research contributions or open-source systems
• Building products or systems that have attracted investor attention, and raised capital successfully

Profile

• Staff / Principal-level AI engineer, or early technical leader within a high-quality AI-native startup, or frontier research environment
• Strong systems thinker with end-to-end architecture capability across model design, infrastructure, and production AI systems
• Comfortable building without large teams or corporate scaffolding
• Experience working with or contributing to frontier AI research environments or open research communities
• Motivated by ownership and long-term equity value
• Capable of representing the technical narrative in investor conversations

What will you do?

• Architect and build the core AI system and technical foundation
• Design scalable applied LLM and agentic workflows aligned to defined commercial use cases
• Translate frontier AI capabilities into production-ready systems
• Contribute to the development of new approaches for applying frontier AI techniques to real-world economic systems.
• Define experimentation frameworks and learning loops that allow systems to improve continuously through real-world feedback
• Define the early infrastructure, evaluation, and optimisation strategy
• Operate as a founder-level technical partner to the CEO
• This role combines deep system design with commercial judgement and long-term platform thinking.

Qualified candidates or referrals are encouraged to apply directly or contact Adrian Schofield for a confidential discussion.

This is a confidential retained search being conducted by Hudson Modeling.