Delivery Lead

i3; Greater London; Ibrido; GBP 120.000 - 180.000; Tempo pieno

Descrizione del lavoro

i3 in London is seeking a senior AI/ML leader to drive production AI/ML initiatives. You will combine hands‑on engineering with delivery leadership, maintaining technical credibility while guiding architecture, reviews and engineering standards.

You’ll lead the design and deployment of Generative AI systems, MLOps practices, and advanced analytics, mentoring data scientists and engineers, and collaborating with data and business stakeholders to scale solutions.

Competenze

• Significant experience delivering AI/ML solutions into production.
• Strong hands‑on technical capability and experience leading technical delivery teams.
• Azure OpenAI / Azure Machine Learning experience would be highly relevant.

Mansioni

• Leading the day‑to‑day technical delivery of AI/ML initiatives, from concept through to production.
• Owning solution architecture, design reviews and production readiness standards.
• Delivering Generative AI solutions, including LLM applications, RAG architectures, prompt engineering and vector search.
• Establishing MLOps practices covering testing, deployment, model lifecycle, monitoring and observability.
• Hands‑on work with Python, Databricks, MLflow, Spark and Azure AI technologies.
• Setting engineering standards around code quality, Git, documentation and production‑ready development.
• Mentoring Data Scientists and AI Engineers through code reviews and architecture reviews.
• Partnering with Data Engineering, Technology and business stakeholders to scale AI opportunities.
• Evaluating emerging technologies including foundation models, agentic AI and orchestration frameworks.
• Acting as a senior deputy within the Data Science & AI leadership team.

Conoscenze

AI/ML leadership

Python

MLOps

Generative AI

LLMs

Vector search

Prompt engineering

Strumenti

Databricks

MLflow

Spark

Azure AI

Descrizione del lavoro

London – hybrid, 3 days per week in the office

Previous insurance or reinsurance experience is required, ideally with exposure to areas such as underwriting, claims, actuarial or other insurance data.

This is a senior, hands‑on leadership position for someone who can combine AI/ML engineering expertise with technical delivery leadership. You’ll help lead the delivery of AI, machine learning and advanced analytics solutions from concept through to production, while remaining close to the technology and code.

This is not a purely managerial role. You’ll be expected to maintain strong technical credibility, contribute to Python‑based development when required, review code and architecture, and set engineering standards across AI delivery.

What you’ll be doing:

• Leading the day‑to‑day technical delivery of AI/ML initiatives, from initial concept through to production
• Owning solution architecture, technical design reviews and production-readiness standards
• Delivering and shaping Generative AI solutions, including LLM applications, RAG architectures, prompt engineering and vector search
• Establishing strong MLOps practices covering testing, deployment, model lifecycle management, monitoring and observability
• Working hands‑on with Python, Databricks, MLflow, Spark and Azure AI technologies
• Setting engineering standards around code quality, Git, documentation and production‑ready development
• Mentoring Data Scientists and AI Engineers through code reviews, architecture reviews and hands‑on technical coaching
• Partnering with Data Engineering, Technology and business stakeholders to turn AI opportunities into scalable production solutions
• Evaluating emerging technologies including foundation models, agentic AI, orchestration frameworks and AI evaluation techniques
• Acting as a senior deputy within the Data Science & AI leadership team

What we’re looking for:

You’ll need significant experience delivering AI/ML solutions into production, alongside strong hands‑on technical capability and experience leading technical delivery teams.

Strong experience with Python, Databricks, MLflow and MLOps is important, together with practical knowledge of LLMs, RAG, vector search and Generative AI. Azure experience – particularly Azure OpenAI, Azure Machine Learning and/or Azure AI Search – would be highly relevant.