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Technical AI Implementation Lead
Greater Manchester (3 days/week onsite)
Salary: £80,000-£100,000
The Opportunity
We are partnering with an ambitious and growing organisation embarking on a significant AI transformation journey. The business is investing heavily in AI to improve operational efficiency, enhance customer experience, and unlock new opportunities for growth.
As the Technical AI Implementation Lead, you will play a pivotal role in building and scaling AI capability across the organisation. This is a senior, hands-on position combining AI strategy, technical implementation, automation, and user enablement.
You will be responsible for identifying high-value AI opportunities, implementing practical solutions, and driving adoption across the business through training, coaching, and best-practice guidance. Acting as a bridge between technology and the wider business, you will work closely with stakeholders at all levels to ensure AI delivers measurable and lasting impact.
This is a rare opportunity to shape AI capability from the ground up, establish best practices, and play a key role in defining how AI transforms the organisation for years to come.
The Role
- Define and execute the organisation's AI implementation and adoption strategy.
- Identify, prioritise, and deliver high-impact AI initiatives across multiple business functions.
- Evaluate, select, implement, and optimise AI tools, platforms, and automation solutions.
- Design and deliver AI-enabled workflows, integrations, and lightweight automations to improve productivity and operational efficiency.
- Build practical AI use cases, prototypes, and proof-of-concepts to demonstrate business value.
- Partner with stakeholders to understand business challenges and translate them into scalable AI solutions.
- Lead the rollout and adoption of AI technologies, ensuring teams are supported through training, coaching, and enablement activities.
- Develop reusable playbooks, frameworks, and best practices to support effective and responsible AI usage.
- Establish governance frameworks, usage policies, and guardrails for AI across the organisation.
- Monitor emerging AI technologies and assess their potential application within the business.
- Act as the internal subject matter expert for AI, providing guidance and support across technical and non-technical teams.
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.
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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.
Essential Requirements
- Demonstrable experience leading AI adoption, digital transformation, or technology enablement initiatives within a commercial environment.
- Strong technical background in software engineering, systems integration, automation, platform engineering, solutions architecture, or a related discipline.
- Hands-on experience implementing and applying AI technologies, including Large Language Models (LLMs) and generative AI tools.
- Experience designing and deploying AI-enabled workflows, automations, and integrations using APIs and modern AI platforms.
- Strong understanding of prompt engineering, evaluation techniques, and the practical application of AI within business environments.
- Experience engaging and influencing stakeholders across both technical and non-technical audiences.
- Excellent communication, facilitation, and change management skills.
- Excellent interpersonal skills, with the ability to engage, coach, and influence both technical and non-technical stakeholders across all levels of the organisation.
- Comfortable operating at both strategic and hands-on levels.


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Desirable Requirements
- Experience with workflow automation platforms such as Power Automate, Zapier, Make, or n8n.
- Experience integrating AI solutions with existing SaaS platforms and business systems.
- Familiarity with cloud AI platforms such as AWS Bedrock, Azure AI, or Google Vertex AI.
- Experience with agentic AI, orchestration frameworks, AI assistants, or multi-agent systems.
- Previous experience within highly operational, customer-centric, or fast-paced environments.
- Experience building communities of practice, AI champion networks, or internal enablement programmes.
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