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GenAI Lead
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a GenAI Lead Engineer (Contract) in London, UK (Hybrid) for 3-6 months. Requires 7+ years in Software/Data/ML Engineering, 2+ years in LLM/Generative AI, strong Python/TypeScript skills, and experience with cloud platforms.
π - Country
United Kingdom
π± - Currency
Β£ GBP
-
π° - Day rate
Unknown
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ποΈ - Date
June 11, 2026
π - Duration
3 to 6 months
-
ποΈ - Location
Hybrid
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π - Contract
Unknown
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π - Security
Unknown
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π - Location detailed
London Area, United Kingdom
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π§ - Skills detailed
#Documentation #Model Evaluation #Data Engineering #TypeScript #GCP (Google Cloud Platform) #Automation #AI (Artificial Intelligence) #Python #Consulting #ML (Machine Learning) #Azure #Docker #AWS (Amazon Web Services) #JavaScript #Security #Databases #Kubernetes #Compliance
Role description
GenAI Lead Engineer (Contract)
Location:Β London, UK (Hybrid)
Duration:Β 3-6 Months
We are looking for an experienced GenAI Lead Engineer to lead the design, prototyping, and implementation of Generative AI solutions for a fast-paced consulting engagement. You'll work closely with business and technical stakeholders to identify opportunities, build PoCs/MVPs, and define a roadmap for future AI adoption.
Key Responsibilities
β’ Identify and prioritise high-impact GenAI use cases.
β’ Design end-to-end AI solution architectures.
β’ Build and deploy PoCs and MVPs, including copilots, chatbots, and AI-powered automation solutions.
β’ Develop RAG pipelines, integrate AI services with enterprise systems, and establish evaluation frameworks.
β’ Define governance, security, privacy, and compliance best practices.
β’ Mentor internal teams and provide documentation, knowledge transfer, and strategic recommendations.
Requirements
β’ 7+ years' experience in Software Engineering, Data Engineering, or ML Engineering.
β’ 2+ years' hands-on experience delivering LLM/Generative AI solutions.
β’ Strong Python and/or TypeScript/JavaScript skills.
β’ Experience with:
β’ LLM frameworks and APIs
β’ RAG architectures and vector databases
β’ AWS, Azure, or GCP
β’ Docker (Kubernetes advantageous)
β’ Strong understanding of prompt engineering, model evaluation, security, and AI governance.
β’ Proven ability to lead technical initiatives and engage with senior stakeholders.
Desirable
β’ Consulting or advisory experience.
β’ Experience with fine-tuning, LLMOps/MLOps tools, and enterprise integrations.
β’ Background in regulated industries such as financial services, healthcare, or telecoms.
GenAI Lead Engineer (Contract)
Location:Β London, UK (Hybrid)
Duration:Β 3-6 Months
We are looking for an experienced GenAI Lead Engineer to lead the design, prototyping, and implementation of Generative AI solutions for a fast-paced consulting engagement. You'll work closely with business and technical stakeholders to identify opportunities, build PoCs/MVPs, and define a roadmap for future AI adoption.
Key Responsibilities
β’ Identify and prioritise high-impact GenAI use cases.
β’ Design end-to-end AI solution architectures.
β’ Build and deploy PoCs and MVPs, including copilots, chatbots, and AI-powered automation solutions.
β’ Develop RAG pipelines, integrate AI services with enterprise systems, and establish evaluation frameworks.
β’ Define governance, security, privacy, and compliance best practices.
β’ Mentor internal teams and provide documentation, knowledge transfer, and strategic recommendations.
Requirements
β’ 7+ years' experience in Software Engineering, Data Engineering, or ML Engineering.
β’ 2+ years' hands-on experience delivering LLM/Generative AI solutions.
β’ Strong Python and/or TypeScript/JavaScript skills.
β’ Experience with:
β’ LLM frameworks and APIs
β’ RAG architectures and vector databases
β’ AWS, Azure, or GCP
β’ Docker (Kubernetes advantageous)
β’ Strong understanding of prompt engineering, model evaluation, security, and AI governance.
β’ Proven ability to lead technical initiatives and engage with senior stakeholders.
Desirable
β’ Consulting or advisory experience.
β’ Experience with fine-tuning, LLMOps/MLOps tools, and enterprise integrations.
β’ Background in regulated industries such as financial services, healthcare, or telecoms.






