AI Enablement Specialist

The Team

Man Group has been at the forefront of applying technology and data science to investment management for over three decades. Today, that legacy is driving a firm-wide AI transformation with over 1,500 employees using our AI platform daily, adoption has reached a critical inflection point and momentum continues to build. We're now hiring an AI specialist to partner with teams across the business, turning that momentum into tangible, measurable outcomes.

This is not a research role. It’s not a pure engineering role. It’s the person who sits at the intersection of business problems and AI capabilities, and makes things happen. You’ll become an expert in how Man Group operates our products, our processes, our systems, our people and use that knowledge to identify where AI creates the most value, then build it, ship it, and help others do the same.

You’ll work across the entire firm: sitting with a Sales team to understand why an RFP takes 5 days, then building a prototype that gets it to 48 hours. Running a workshop with Legal to map their document review process, then designing an AI workflow that halves the time. Helping a Portfolio Manager understand what Claude Code can do for their research process, then pairing with them to build it.

You’ll shape the role, the approach and help drive strategy.

We’re looking for someone who: 

• Gets energy from solving other people’s problems, not just their own 

• Is curious about how a business actually works the messy reality, not the org chart 

• Can context-switch between a deeply technical conversation and a commercial one in the same meeting 

• Has the confidence to challenge senior stakeholders constructively and the humility to learn from them 

• Sees AI as a tool for making people more capable 

Role Responsibilities

Accelerate education and engagement

• Become the person people come to when they want to understand what’s possible with AI at Man
• Run workshops, pair-building sessions, and demos that turn sceptics into users and users into builders
• Help leaders in each business unit define their highest-value AI projects and build the skills to deliver them
• Create reusable patterns, templates, and playbooks that scale your impact beyond 1:1 engagements

Solve real business problems with AI

• Embed with business units to understand their processes, pain points, and opportunities at a detailed level
• Rapidly prototype AI-powered solutions using Python, LLM APIs (Anthropic Claude, OpenAI), and the MAIA platform (our internal platform)
• Build end-to-end: from scoping the problem with stakeholders through to a working tool they can use
• Focus on time-to-value: ship early, iterate fast, measure outcomes

Drive process transformation

• Map end-to-end business processes (client lifecycle, reporting chains, operational workflows) and identify where AI creates the highest leverage
• Design AI-first workflows that don’t just automate the existing process but reimagine it
• Work with the strategy team to deliver cross-cutting improvements that benefit multiple business units
• Build the business case: define metrics, measure before and after, present outcomes to leadership

Build the AI product knowledge

• Become an expert in MAIA’s capabilities: what it can do today, what’s on the roadmap, where the gaps are
• Stay current on AI tooling, techniques, and best practices and translate them into practical applications for Man
• Bridge between the AI engineering team (who build the platform) and the business (who use it) translating requirements in both directions
• Contribute to the platform: build skills, integrations, and workflows that become part of MAIA’s shared capability

Key Competencies

Essential

• 5–8 years’ experience in roles that combined technical delivery with business problem-solving. Could be: AI/ML engineering with client-facing work, management consulting with a technical edge, product management for AI/data products, or solutions engineering at a technology company.
• Python skills. You don’t need to be a systems engineer, but you must be able to build prototypes, work with APIs, process data and help design features.
• Hands-on experience with LLMs. You’ve built things with Claude, GPT, or equivalent. You understand prompting, RAG, tool use, agents, and the practical limitations. You know when AI is the right tool and when it isn’t.
• Exceptional stakeholder skills. You can sit with a senior portfolio manager, a head of operations, or a sales lead and earn their trust. You listen before you solve. You communicate clearly to technical and non-technical audiences.
• Bias for action. You’d rather ship a working prototype in a week than a perfect specification in a month. You’re comfortable operating with ambiguity and making progress without waiting for permission.
• Systems thinking. You can look at a business process and see the system: inputs, transformations, outputs, feedback loops, bottlenecks. You think in workflows, not features.

Advantageous

• Financial services experience particularly asset management, investment operations, or capital markets
• Experience with enterprise AI deployments at scale (not just experiments)
• Familiarity with MCP (Model Context Protocol), agent frameworks, or AI workflow orchestration
• Experience training or educating others on AI tools and techniques
• Understanding of data engineering: pipelines, integrations, data quality, metadata management