Location: Central London Hybrid (3 Days Onsite per Week)
Opportunity Overview
A global organisation is building a centralised AI enablement and platform engineering function focused on delivering scalable secure and governed AI capabilities across the enterprise.
This role sits within a programme delivering enterprise-grade agentic AI infrastructure including internal AI assistants retrieval and search services extensibility frameworks and governance tooling.
Programme Overview
The programme is focused on delivering a production-grade internal agentic AI platform including:
Development of an enterprise AI assistant capable of reasoning planning and tool orchestration
Operation of enterprise retrieval search and grounding services for approved data sources
Delivery of a secure internal gateway layer providing discovery observability policy enforcement and lifecycle management for AI-integrated services
Design and development of AI-integrated services and reusable capabilities that safely expose internal and third-party systems to AI agents
Establishment of evaluation governance and quality-control frameworks to support scalable and compliant deployment of AI capabilities
The programme currently follows a centrally delivered model while evolving towards a federated contribution approach over time.
Key Responsibilities
Define and implement evaluation frameworks covering correctness safety reliability and regression impact for AI-integrated services
Develop and maintain automated test pipelines for agentic workflows including tool orchestration and multi-step execution paths
Identify evaluate and mitigate AI system failure modes such as hallucinations invalid inputs latency issues and inappropriate tool usage
Produce testing and governance evidence required for internal approval and operational processes
Collaborate closely with ML Engineers and platform teams to embed testability and evaluation capabilities into AI services
Contribute to the long-term quality assurance and governance strategy for enterprise-wide AI platform adoption
Essential Skills and Experience
Strong Python development experience particularly for automation and test frameworks
Experience with LLM and RAG evaluation tooling frameworks or custom evaluation pipelines
Expertise in automated testing across unit integration and regression testing environments
Good understanding of agentic AI systems associated risks and operational failure modes
Ability to assess technical solutions against governance audit and security requirements
Experience working within regulated or highly governed engineering environments
Whats on Offer
Opportunity to contribute to large-scale enterprise AI transformation initiatives
Exposure to cutting-edge AI platform engineering and governance challenges
Collaborative environment working alongside platform engineers ML specialists and architecture teams
Influence over the development of long-term AI quality and governance standards
Opportunity to shape scalable AI engineering practices within a complex enterprise environment
Required Experience:
IC
Job DescriptionQuality Engineer - AI Platform EngineeringEmployment Type: Inside IR35 ContractDuration: 6 MonthsRate: 650 - 750/ DayLocation: Central London Hybrid (3 Days Onsite per Week)Opportunity OverviewA global organisation is building a centralised AI enablement and platform engineering funct...
Job Description
Quality Engineer - AI Platform Engineering
Employment Type: Inside IR35 Contract
Duration: 6 Months
Rate: 650 - 750/ Day
Location: Central London Hybrid (3 Days Onsite per Week)
Opportunity Overview
A global organisation is building a centralised AI enablement and platform engineering function focused on delivering scalable secure and governed AI capabilities across the enterprise.
This role sits within a programme delivering enterprise-grade agentic AI infrastructure including internal AI assistants retrieval and search services extensibility frameworks and governance tooling.
Programme Overview
The programme is focused on delivering a production-grade internal agentic AI platform including:
Development of an enterprise AI assistant capable of reasoning planning and tool orchestration
Operation of enterprise retrieval search and grounding services for approved data sources
Delivery of a secure internal gateway layer providing discovery observability policy enforcement and lifecycle management for AI-integrated services
Design and development of AI-integrated services and reusable capabilities that safely expose internal and third-party systems to AI agents
Establishment of evaluation governance and quality-control frameworks to support scalable and compliant deployment of AI capabilities
The programme currently follows a centrally delivered model while evolving towards a federated contribution approach over time.
Key Responsibilities
Define and implement evaluation frameworks covering correctness safety reliability and regression impact for AI-integrated services
Develop and maintain automated test pipelines for agentic workflows including tool orchestration and multi-step execution paths
Identify evaluate and mitigate AI system failure modes such as hallucinations invalid inputs latency issues and inappropriate tool usage
Produce testing and governance evidence required for internal approval and operational processes
Collaborate closely with ML Engineers and platform teams to embed testability and evaluation capabilities into AI services
Contribute to the long-term quality assurance and governance strategy for enterprise-wide AI platform adoption
Essential Skills and Experience
Strong Python development experience particularly for automation and test frameworks
Experience with LLM and RAG evaluation tooling frameworks or custom evaluation pipelines
Expertise in automated testing across unit integration and regression testing environments
Good understanding of agentic AI systems associated risks and operational failure modes
Ability to assess technical solutions against governance audit and security requirements
Experience working within regulated or highly governed engineering environments
Whats on Offer
Opportunity to contribute to large-scale enterprise AI transformation initiatives
Exposure to cutting-edge AI platform engineering and governance challenges
Collaborative environment working alongside platform engineers ML specialists and architecture teams
Influence over the development of long-term AI quality and governance standards
Opportunity to shape scalable AI engineering practices within a complex enterprise environment