Principal Systems Architect AI Platforms

Luminous Executive Advisory & Strategy; Greater London; Hybrid; GBP 120,000 - 160,000; Full time

Job summary

Luminous Executive Advisory & Strategy seeks a Senior AI Platform Architect to design and own an AI-enabled platform in a remote-friendly setup serving clients in the UK. You will ensure data foundations, model orchestration, and intelligent services align with governance and scale constraints.

The role requires deep expertise in distributed systems and AI infrastructure, with a track record of production systems where ML is integral to core workflows.

Qualifications

• Senior architect or engineer with experience building AI-enabled platforms.
• Deep understanding of distributed systems and AI infrastructure.
• Production systems where ML models are part of core workflows.

Responsibilities

• Design and evolve architecture for data ingestion, storage, and access.
• Model training, deployment, and orchestration.
• AI-driven services and decision-support systems.
• Define how multiple model types interact in a single system (statistical, ML, causal).
• Automation and decision-support.
• Intelligence and human authority.
• Anticipate scaling, safety, and failure modes of AI-enabled systems.
• Guide architectural trade-offs to support long-term evolution and restraint.

Skills

AI architecture

Distributed systems

AI infrastructure

Governance

Job description

LOCATION

Remote | London

ROLE

Role Purpose

You design the AI platform as a system, ensuring that models, data, reasoning, and humans work together coherently over time.
Your role is to maintain architectural integrity as capabilities scale, complexity increases, and use cases expand.

What You’ll Build & Own

You own the end-to-end architecture of the AI platform, from data foundations to intelligence layers and interfaces.

Key Responsibilities

Design and evolve architecture for:

Data ingestion, storage, and access

Model training, deployment, and orchestration

AI-driven services and decision-support systems

Define how multiple model types interact in a single system (statistical, ML, causal)

Automation and decision-support

Intelligence and human authority

Anticipate scaling, safety, and failure modes of AI-enabled systems

Guide architectural trade-offs to support long-term evolution and restraint

Who You Are

Senior architect or engineer with experience building AI-enabled platforms

Deep understanding of distributed systems and AI infrastructure

Has designed production systems where ML models are part of core workflows

Thinks beyond individual components to AI systems as a whole

Values constraints, clarity, and governance as much as capability