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AI Enablement Lead [gn] Data Intelligence

United Kingdom
Posted about 23 hours ago
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AI Enablement Lead [gn] Data Intelligence

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI Enablement Lead [gn] Data Intelligence based in United Kingdom.

This role is designed for a hands-on AI leader who will drive the adoption and scaling of artificial intelligence capabilities across an innovative data technology environment.

You will define the strategy, architecture, and operational frameworks that enable teams to build and deploy AI-powered solutions efficiently and responsibly.

The position combines software engineering expertise, AI infrastructure knowledge, and organizational influence to accelerate product innovation.

You will create reusable AI platforms, establish LLMOps and governance practices, and help engineering teams integrate advanced AI capabilities into production systems.

Working across product, engineering, and business teams, you will transform AI from an emerging technology into a core organizational capability.

This is an opportunity to shape the future of intelligent data platforms while building scalable solutions with measurable business impact.

Accountabilities

As an AI Enablement Lead, you will own the development and execution of AI enablement initiatives, creating the foundations that allow teams to safely and effectively leverage AI technologies. You will combine technical leadership with strategic vision to accelerate AI adoption, improve engineering workflows, and deliver next-generation intelligent capabilities.

  • Design and maintain internal AI platforms, orchestration layers, API gateways, and reusable frameworks including advanced RAG architectures and agentic AI solutions.
  • Partner with product and engineering teams to integrate production-ready generative AI and machine learning capabilities into data platform solutions.
  • Establish LLMOps and MLOps practices, including governance frameworks, model evaluation processes, monitoring systems, security controls, and privacy standards.
  • Optimize AI infrastructure performance by managing model costs, token usage, latency, and technology choices across commercial and open-source solutions.
  • Lead AI enablement initiatives through workshops, technical documentation, architecture guidance, and knowledge-sharing programs.
  • Drive rapid AI prototyping from proof of concept through production deployment, ensuring solutions are scalable, reliable, and maintainable.
  • Define standards for AI tooling, including vector databases, embedding strategies, semantic search approaches, and caching mechanisms.
  • Evaluate emerging AI technologies, vendors, and open-source models to maintain a forward-looking AI strategy.
  • Establish measurable success metrics for AI adoption, including developer productivity, delivery acceleration, and business impact.

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.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your 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.

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It 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.

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Strong

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.

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Strong

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.

Requirements

The ideal candidate is a highly technical AI professional with experience building enterprise-grade AI solutions and the ability to influence teams through strong communication and technical leadership. You should combine software engineering discipline with deep knowledge of modern AI architectures and operational practices.

  • Strong experience as a Senior AI/ML Engineer, LLMOps Engineer, Machine Learning Engineer, or Software Architect building and scaling AI-powered applications.
  • Proven expertise in enterprise SaaS environments, complex data platforms, or large-scale software ecosystems.
  • Advanced knowledge of Python or Go, semantic search, vector databases such as Pinecone, Milvus, or pgvector, and AI orchestration frameworks including LangChain or LlamaIndex.
  • Experience with large language models, prompt engineering, fine-tuning approaches, and building reliable AI-powered workflows.
  • Strong software engineering practices, including CI/CD, automated testing, evaluation datasets, Docker, Kubernetes, and clean architecture principles.
  • Experience designing AI governance frameworks focused on security, privacy, performance, and responsible AI adoption.
  • Ability to proactively identify opportunities and build solutions that address organizational challenges before they become blockers.
  • Excellent leadership and communication skills, with the ability to align cross-functional teams without direct management responsibility.
  • Strong written and verbal English communication skills, with the ability to translate complex AI concepts into clear business value.

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Benefits

  • Opportunity to lead AI transformation initiatives within an innovative and fast-growing technology environment.
  • Competitive salary and benefits package.
  • Flexible work arrangements, including remote or hybrid options.
  • Collaboration with a diverse and highly skilled team of technology professionals.
  • Opportunities for professional growth, continuous learning, and career development.
  • The chance to shape AI strategy, tooling, and product innovation at scale.

How Jobgether Works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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Skills

AI Leadership
Software Engineering
AI Infrastructure
Generative AI
Machine Learning
Python
Go
Semantic Search
Vector Databases
MLOps
LLMOps
AI Governance
CI/CD
Docker
Kubernetes
Clean Architecture

Location

United Kingdom

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