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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.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
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


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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.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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