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Technology Lead, AI Lab

167 Solutions Ltd·London (South East England)HybridLead
£150 000 – £200 000 / year
Vox Summary
  • Role Responsibilities: Design, build, deploy, and iterate enterprise-scale Generative AI systems, including RAG pipelines, agent workflows, and API integrations.
  • Key Skills & Experience: Minimum 3 years in Generative AI or applied ML, with hands-on coding, deployment, and experience with LLM ecosystems, prompt engineering, and cloud platforms.
  • Technical Focus: Work extensively with open-source and commercial LLMs, vector databases, orchestration patterns, and MLOps practices including versioning and bias management.
  • Conditions & Benefits: Hybrid working model, greenfield projects with freedom to architect solutions, and opportunities for career progression within a growing Centre of Excellence.
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Job description

Location: UK (Hybrid – 1–2 days per week onsite) Employment Type: Permanent Right to Work: Must already have the right to work in the UK (no sponsorship) About 167 Solutions 167 Solutions is a UK-based specialist technology recruitment and consultancy partner. We work closely with high-growth consultancies and enterprise clients to identify engineers who want to build meaningful systems, not just maintain them. We are hiring on behalf of our client and managing the process end to end hiring. The Role 167 Solutions is partnering with a high-growth consultancy making a significant multi-year investment into Generative AI. This hire is critical. You will be one of the core technical leaders, responsible for hands-on delivery from day one, while also helping shape a new Generative AI Centre of Excellence (CoE). This is not a strategy-only or advisory role. This is a 24/7 hands-on engineering role, building, testing, deploying, and iterating production-grade GenAI systems at enterprise scale. Everything is greenfield. No legacy constraints. No pre-selected vendors. You will help define the technical direction, tooling, and engineering standards while actively writing code and shipping solutions. What You’ll Be Doing (Hands-On) • Design, build, and deploy Generative AI systems end to end – from use-case discovery through to production • Build Retrieval-Augmented Generation (RAG) pipelines using vector databases, embeddings, and enterprise data sources • Develop agent-based workflows, orchestration layers, and multi-step reasoning systems • Work extensively with open-source and commercial LLM ecosystems, including Hugging Face models and tooling • Implement prompt engineering, evaluation frameworks, and performance optimisation strategies • Architect secure, scalable GenAI solutions on AWS and GCP • Build APIs, services, and pipelines to integrate GenAI into real business workflows • Apply LLMOps / MLOps practices: versioning, monitoring, cost control, bias, and drift management • Work directly with clients to translate business problems into deployable AI solutions, not slide decks • Contribute to building internal IP, accelerators, and reusable frameworks as the CoE scales What We’re Looking For • Minimum 3 years’ experience building and deploying Generative AI or applied ML systems • Strong hands-on engineering background – you actively code, build, test, and deploy • Experience with: • RAG architectures and vector databases • Hugging Face models, pipelines, and inference tooling • Prompt engineering and LLM evaluation techniques • Agentic systems and orchestration patterns • Cloud-native experience across AWS and/or GCP • Comfortable working across multiple business functions (finance, ops, customer, HR, tech, data) • Platform-agnostic mindset – focused on methodology, workflow, and outcomes, not vendor lock-in • Consulting mindset: able to engage stakeholders while staying deeply technical • Experience operating at Senior / Lead / Manager level, or as the go-to GenAI engineer on projects Why This Opportunity Stands Out • Hands-on by design – this is a builder’s role, not a steering committee role • Greenfield GenAI practice with genuine freedom to architect properly • Heavy investment committed over the next 2 years • Enterprise-scale builds with real users, real data, and real impact • Clear progression as the CoE grows in size and capability • Hybrid working that balances autonomy with collaboration

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Original source
reed.co.uk
Posted
Jun 03, 2026 · true date
Last verified
2 hours ago
Quality score
65/100
Salary stated30
Company identified0
applyUrl0
postedAt15
Complete description20

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