Founding Engineer

Founding AI Engineer

Location: London (Hybrid / Flexible)
Salary: Competitive DOE + Bonus + Equity

Company Overview

We are working with an early-stage technology company building AI-native systems that help large organisations better understand, govern, and secure complex data and identity ecosystems.

Operating at the intersection of AI, cyber security, and enterprise data platforms, the business is focused on transforming how organisations model access, risk, and data relationships across increasingly distributed cloud environments.

The team is small, highly technical, and product-focused, with a strong bias toward ownership, rapid iteration, and building systems that operate in complex, real-world enterprise environments. Engineering sits at the centre of everything, and individuals are expected to have a direct impact on product direction and architecture.

The Role

We are seeking a Founding AI Engineer / Engineering Lead to join the business at a pivotal stage as the platform moves from early MVP into scalable production use with enterprise customers.

This is a hands-on technical leadership role, not a product management position.

You will be responsible for designing, building, and scaling core components of an AI-driven enterprise platform, working across data, machine learning, and distributed systems. You will also work directly with early customers to understand real-world use cases and translate them into robust, scalable product capabilities.

This role suits someone who still enjoys building and shipping code, but is comfortable influencing architecture, mentoring engineers, and shaping technical direction.

You will have significant influence over:

• Core system architecture
• AI/ML strategy and implementation
• Data modelling and enterprise integration patterns
• Early product design decisions
• Engineering standards and scalability approach

Key Responsibilities

• Design and build core components of an AI-native enterprise platform from the ground up
• Develop and deploy machine learning and LLM-based systems in production environments
• Build scalable data and AI pipelines across complex enterprise datasets
• Work closely with early enterprise customers to refine requirements and shape product direction
• Define and implement system architecture for AI, data, and integration layers
• Build agentic AI workflows and knowledge-driven systems using modern LLM frameworks
• Implement robust MLOps pipelines for model training, deployment, monitoring, and governance
• Contribute directly to production code in Python and related AI/data tooling
• Support technical decision-making around cloud architecture, scalability, and system design
• Help establish engineering best practices in a fast-moving early-stage environment

Tech Stack

• Python
• TensorFlow / PyTorch
• LLM frameworks (LangChain, LangGraph, or similar agentic AI tooling)
• AWS / Azure cloud platforms (including AI services such as Bedrock)
• Data engineering tools (e.g. AWS Glue or equivalent)
• NLP, embeddings, vector databases, RAG architectures
• MLOps tooling for model deployment and monitoring
• Experience with distributed data systems and APIs

Required Skills & Experience

• Several years' experience in software engineering, data engineering, or AI engineering roles
• Strong academic background in Computer Science, Engineering, Mathematics, or similar
• Experience working in a product-led technology environment (SaaS, AI platform, or similar)
• Proven ability to ship production-grade AI or data systems
• Strong Python engineering capability
• Experience with modern ML / LLM systems and frameworks
• Exposure to cloud-based AI/ML platforms (AWS, Azure, or GCP)
• Comfortable working in early-stage environments with ambiguity and ownership
• Strong communication skills and ability to work directly with technical and non-technical stakeholders

Bonus Experience (Highly Valued)

• Cyber security / identity / access management (IAM / IdAM) exposure
• Cloud operations, DevSecOps, or infrastructure-heavy environments
• Experience in regulated or enterprise-scale domains
• Knowledge of enterprise data governance, data modelling, or integration architecture

How You Work

• Highly hands-on and enjoys building systems end-to-end
• Comfortable operating in ambiguity and shaping problems as well as solving them
• Strong bias toward delivery, iteration, and practical engineering outcomes
• Collaborative, but able to take full ownership of technical decisions
• Interested in building foundational systems, not just features

What We Offer

• Highly competitive base salary (DOE) + bonus
• Equity / stock options in a high-growth early-stage business
• Private medical insurance
• Hybrid working (London-based, flexible model)
• High ownership role with significant influence on product and architecture

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