AI Platform Lead

TL;DR

AI Platform Lead (AI/ML): Own the definition, creation, and ongoing management of enterprise AI platform and roadmap with an accent on platform reliability, security, governance, and scale. Focus on defining standards, reference architectures, guardrails, providing architectural coaching, and driving enterprise innovation through AI capabilities including agentic workflows, RAG/Graph-RAG pipelines, and LLM-powered applications.

Location: Fully remote and may be based in United Kingdom, Ireland, Spain, or Poland, subject to valid work authorisation.

Salary: For Poland the starting salary is 223.300-297.700 PLN gross, varies by location and local market conditions; eligible for annual bonus with 20% target payout of base salary.

Company

A global leader in applied safety science transforming safety, security, and sustainability challenges into opportunities through testing, inspection, certification, software products, and advisory offerings.

What you will do

• Own the enterprise AI platform definition, creation, roadmap, standards, reference architectures, guardrails, and quality processes.
• Provide architectural coaching to squads, mentor technical contributors, and set technical direction for AI capabilities informing product strategies.
• Collaborate with business stakeholders, cyber security, enterprise architecture, risk & compliance, and vendors to align platform to business needs and accelerate adoption.
• Lead architecture for AI/ML systems including agentic workflows, RAG/Graph-RAG, knowledge-graph retrieval, vector search, and LLM applications.
• Ensure enterprise-grade scalability, resilience, global availability, observability, cost management, and Responsible AI standards.
• Mentor across AI/ML, platform, and full-stack engineering; drive operational excellence, issue remediation, and lifecycle strategies for AI solutions.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Machine Learning, or related (Master’s preferred) with current cloud architecture certification.
• Extensive experience leading AI/ML architecture, technical strategies, roadmaps, and modern AI patterns like agentic frameworks, RAG/Graph-RAG, vector search, safety guardrails.
• Strong Azure cloud knowledge including identity/security, networking, Kubernetes, governance, observability, CI/CD, and AI Foundry.
• Proven ability to define standards, lead reviews, drive adoption of scalable/secure patterns, Agile practices.
• Excellent communication, stakeholder collaboration, leadership, and mentoring skills.

Culture & Benefits

• Annual paid leave, access to ULS University for continuous learning and career growth.
• Two volunteering days per year for community activities.
• Flexible working arrangements to balance work and life.
• Global community focused on innovation, safety science, and sustainability.
• Investment in training, empowering people to learn and innovate.