AI Engineering Subject Matter Expert – Contract
peopleworth
contract
Posted on:
Location Type: Remote
Location: United Kingdom
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About the role
- Develop technical source material for multiple sequential learning modules including code examples, system architecture references, case studies, assessment briefs, and worked solutions
- Collaborate with learning designers to translate curriculum frameworks into technically accurate and production-relevant learning content
- Participate in collaborative curriculum design sessions with academic contributors to refine programme scope, sequencing, and exit standards
- Review learning materials throughout the development process to ensure technical accuracy, credibility, and alignment with current industry practices
- Design summative assessments that reflect real-world AI engineering hiring and evaluation formats
- Provide practitioner insight into the design of production AI application architectures and engineering workflows
- Contribute expert insights to live masterclass or knowledge-sharing sessions following programme launch
- Advise on the practical realities of building and deploying production AI applications, including common failure modes and operational challenges
- Support the development of content covering evaluation methodologies, reliability patterns, governance considerations, and architectural decision-making for AI applications
Requirements
- Demonstrated experience building and deploying production AI systems powered by large language models in recent industry environments
- Strong software engineering foundations including testing practices, CI/CD pipelines, observability, and reliability engineering approaches
- Practical experience implementing LLM-based application architectures including API integrations, prompt strategies, and structured outputs
- Hands-on experience with retrieval-augmented generation pipelines including embedding models, vector databases, hybrid search approaches, and retrieval evaluation
- Familiarity with agent-based architectures including planning loops, memory strategies, tool integrations, and cost management patterns
- Experience designing evaluation frameworks for AI applications including automated evaluation methods, regression testing approaches, and performance monitoring
- Understanding of responsible AI practices including bias considerations, governance documentation, and auditability
- Experience mentoring engineers, hiring technical talent, or assessing engineering capability in AI-related roles
- Ability to collaborate effectively with technical and academic contributors on curriculum and learning design
- Professional experience demonstrating subject expertise equivalent to postgraduate level knowledge in AI engineering or related fields
Benefits
- Collaborative, people-centred performance culture
- Opportunities to grow in a fast-paced environment
- Flexible remote working arrangements
- Opportunity to contribute expertise to the development of high-impact professional learning experiences
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
AI systemslarge language modelssoftware engineeringtesting practicesCI/CD pipelinesobservabilityreliability engineeringLLM-based application architecturesretrieval-augmented generationevaluation frameworks
Soft Skills
collaborationmentoringcommunicationcurriculum designsubject expertise