Lead AI Engineer
- Salary
- Not stated
- Level
- Lead
- Work type
- Hybrid · London
- Visa
- Not stated
Open. First seen 10 October 2026.
The team: Engineering
This role is one of 4 open in Engineering.
WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS
Python (4 of 4), AWS (3 of 4), Azure (3 of 4), Vector Databases (3 of 4), CI/CD (2 of 4), Docker (2 of 4), Kubernetes (2 of 4)
OTHER ROLES ON THIS TEAM
- Principal Software Engineer posted Mar 20
- Principal AI Engineer posted Mar 20
- Data Platform Engineer posted Oct 3
From the team and dates on WeBuild-AI's own job board.
About the role
About WeBuild-AI:
WeBuild-AI are AI natives delivering 10x value for enterprise organisations. We combine highly skilled experts with our AI Launchpad, industry-aligned language models, and agents to transform enterprise organisations into AI-powered and data-driven businesses. We work with enterprise organisations on a global stage, reinventing how they design, build, and operate AI powered software at scale with speed.
Our Purpose:
We're on a mission to reinvent what's possible with AI in enterprise environments. Our AI Engineers don't just implement solutions—they discover new patterns of working with AI that revolutionise entire business processes. We believe AI will fundamentally transform how organisations operate, and we're looking for pioneers who want to lead this transformation, working at the absolute cutting edge of what's possible with today's most advanced AI technologies.
Role Overview:
As a Lead AI Engineer at WeBuild-AI, you will design, develop, and deploy innovative AI solutions that transform our clients' businesses. You'll leverage cutting-edge language models, agent frameworks, and our Pathway platform to create high-impact AI applications that deliver 10x value. You'll be given the freedom to experiment and push boundaries, discovering new ways AI can solve complex enterprise challenges.
Key Responsibilities
- Lead the design and development of AI solutions using language models and agent frameworks.
- Implement and customise agent frameworks such as Autogen and LangGraph for production-grade systems.
- Integrate AI capabilities with client systems, digital products, and data sources in collaboration with data engineers.
- Translate client requirements into scalable, secure, and high-performing AI applications.
- Oversee technical quality across project teams, mentoring mid-level and junior engineers.
- Support clients with AI adoption, education, and safe implementation practices.
- Contribute to the evolution of our internal AI delivery platform (Pathway) and engineering standards.
- Stay current with emerging AI tools and frameworks, introducing improvements to team workflows.
Required Skills & Experience
- Proven experience designing and deploying production-grade AI/ML or LLM systems.
- Expertise with AWS or Azure AI services (e.g., Bedrock, SageMaker, OpenAI, Cognitive Services).
- Strong Python programming skills with hands-on experience using frameworks like Autogen and LangGraph.
- Solid grounding in MLOps, containerisation (Docker, Kubernetes), and vector databases.
- Understanding of agent monitoring tools (Langfuse, OpenTelemetry).
- Strong software engineering best practices (testing, CI/CD, code reviews).
- Excellent communicator able to work with cross-functional teams and clients.
- Desire to experiment, iterate, and push the boundaries of practical AI.
The Mindset We Value:
Relentless Innovation:
We're looking for individuals who are constantly exploring the edges of what's possible with AI. You should be the type who stays up late testing new approaches just to see what might work.
Flexible Methodology:
Traditional development approaches don't always apply to AI. We need people who can adapt their working methods to the unique characteristics of AI systems, embracing experimental approaches when appropriate.
"Can Do" Attitude:
When faced with a seemingly impossible challenge, your response should be "let's figure out how" rather than "it can't be done." We value determined problem-solvers who find a way forward.
Balanced Perspective:
While pushing boundaries, you must maintain a grounded understanding of enterprise realities, balancing innovation with practical implementation.
Growth Opportunities:
- Develop expertise with emerging AI models and capabilities before they reach mainstream adoption.
- Create intellectual property and novel implementation approaches.
- Work across multiple industries to develop deep domain expertise.
- Contribute to the evolution of our proprietary AI methodology.
- Participate in the AI research community and establish thought leadership.
- Shape new AI services and capabilities within our Pathway platform.
This role is hybrid and we come into our London based office 3 days a week.
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