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GenAI Lead

⭐ - 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.
🌎 - Country
United Kingdom
πŸ’± - Currency
Β£ GBP
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πŸ’° - Day rate
Unknown
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πŸ—“οΈ - Date
June 11, 2026
πŸ•’ - Duration
3 to 6 months
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🏝️ - Location
Hybrid
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πŸ“„ - Contract
Unknown
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
London Area, United Kingdom
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🧠 - 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.