Gen AI Solutions Lead
Company
Location
London, England, United Kingdom
Posted At
7/30/2025
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Description
Key Responsibilities
Permanent
- Lead the design and delivery of production-grade GenAI solutions using LLMs, RAG, and vector search, optimising prompts, context, and retrieval for accuracy and performance.
- Architect and implement GenAI services integrated with enterprise systems and cloud platforms, ensuring scalability, security, and maintainability.
- Own the delivery of GenAI applications such as internal support assistants, case handling tools, and commercial automation services.
- Deliver solutions from proof-of-concept to production, focused on measurable business value while meeting compliance and performance standards.
- Collaborate with cross-functional teams to embed GenAI into operational and commercial workflows as part of wider digital transformation efforts.
- Lead technical workshops and enablement sessions to support internal adoption of GenAI tools and practices.
- Evaluate GenAI APIs, frameworks, and vendors, advising on architecture, integration strategy, and build-vs-buy decisions.
- Implement monitoring and evaluation processes to ensure solution quality, reliability, and continuous improvement.
- Partner with security and governance teams to ensure responsible, compliant deployment of GenAI technologies.
- Proven experience leading the development and deployment of GenAI systems in enterprise environments.
- Deep hands-on expertise with LLMs, RAG architectures, vector databases, and orchestration frameworks (e.g. LangChain).
- Strong understanding of prompt design, context management, and GenAI-specific risks such as hallucination and data exposure.
- Experience integrating GenAI solutions with enterprise systems and cloud platforms (AWS, Azure, or GCP).
- Proven ability to work independently and collaboratively across technical and business teams to deliver outcomes with clear business impact.
- Excellent communication and stakeholder engagement skills, particularly in cross-functional environments.
- Background in software engineering, ML engineering, or AI solution architecture.
- Familiarity with CI/CD, observability, and MLOps practices that support scalable GenAI deployment.
- Experience working in large-scale or regulated enterprise settings.
- Proven track record delivering GenAI solutions across knowledge assistants, customer support, commercial automation, and engineering tools.
- Understanding of evaluation methods for GenAI in production environments, including user feedback loops, latency tracking, and quality scoring.
- Exposure to advanced GenAI orchestration patterns and frameworks such as tool use, memory management, agentic workflows, or Model Context Protocol.
Permanent
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