WeBuild-AI

AI engineer for enterprise software

In short

Lead-level AI engineering role defining enterprise AI architecture and technology strategy, leading technical direction across multiple teams and mentoring Lead AI Engineers. Posted by an AI consultancy that builds AI-powered and data-driven enterprise software for global clients. Requires deep experience architecting enterprise-grade AI/ML systems, expertise with cloud AI ecosystems (AWS Bedrock, SageMaker, Azure OpenAI, Azure ML), agent frameworks, vector databases, LLM orchestration, and advanced Python/MLOps skills. Hybrid role based in London, 3 days a week in office.

About
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.
Responsibilities
•Define the overall AI architecture and technology strategy, ensuring long-term scalability and reliability.
•Lead technical direction across multiple teams, overseeing the full AI solution lifecycle — from concept to production.
•Mentor and guide Lead AI Engineers and technical contributors to raise the engineering bar.
•Champion best practices for governance, observability, and lifecycle management of AI systems.
•Evaluate and introduce emerging frameworks, including Autogen, LangGraph, and other agentic ecosystems.
•Partner with senior stakeholders to align AI strategy with business goals.
•Drive the evolution of our internal platform (Pathway) to enable faster, safer AI delivery.
•Represent the company externally as a technical authority — at client workshops, conferences, or thought leadership sessions.
•Proactively identify and mitigate risks in AI adoption, ensuring ethical and compliant implementation.
Requirements
•Deep experience architecting and scaling enterprise-grade AI/ML systems.
•Proven expertise with cloud AI ecosystems (AWS Bedrock, SageMaker, Azure OpenAI, Azure ML).
•Strong command of agent frameworks, vector databases, and LLM orchestration tools.
•Ability to lead multi-disciplinary teams and manage complex AI projects.
•Advanced proficiency in Python, MLOps, and software engineering principles.
•Experience setting technical standards, governance frameworks, and performance benchmarks.
•Strong consulting mindset with the ability to translate emerging technology into business impact.
•Strategic thinker with the ability to pioneer new approaches and challenge conventional wisdom.
•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.
•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.
•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.
•While pushing boundaries, you must maintain a grounded understanding of enterprise realities, balancing innovation with practical implementation.
Conditions
•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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