AI Solutions Business Analyst in Cheshire, Warrington

Location: Manchester, England (Hybrid - 3 days per week in office) with occasional workshops and in-person meetings

Salary: Competitive, based on experience

About the role

We’re looking for a practical, customer-focused and AI-curious Business Analyst to help us design and deliver AI agent solutions for our customers. This is not a standard BA role where you simply gather requirements and pass them on. You’ll work with customers to understand their business processes, service challenges, operational pain points and customer journeys, then help shape how AI agents can support, automate or improve those workflows.

You’ll sit between customers, Customer Success, Product and Engineering. Your job will be to turn messy business problems into clear, structured requirements that can be delivered as effective AI-powered agents, workflows, integrations, knowledge sources and customer experiences.

You do not need to be a machine learning engineer or a software developer. However, you do need to demonstrate comfort working with AI tools, understanding how AI agents behave, thinking critically about risk and quality, and helping customers move from vague ideas to practical, testable solutions.

This role is ideal for someone who has experience in business analysis, solution design, implementation, digital transformation, customer operations or SaaS delivery, and who wants to apply those skills in the fast-growing area of AI agents.

What you’ll do

• Lead discovery sessions with customers to understand business goals, operational workflows, customer journeys and pain points.
• Translate customer problems into clear AI agent use cases, requirements, workflows and acceptance criteria.
• Identify where AI agents can improve speed, consistency, customer experience, operational efficiency or employee productivity.
• Map current-state and future-state processes, highlighting where automation, AI assistance or human handoff should occur.
• Define agent behaviours, conversation flows, business rules, escalation paths, knowledge requirements and success measures.
• Work with Junior AI Agent Builders, implementation colleagues and technical teams to ensure requirements are understood and delivered correctly.
• Help design prompts, knowledge structures, test scenarios and evaluation criteria for AI agents.
• Support customer workshops, demos, playback sessions and feedback reviews.
• Challenge vague or unrealistic requirements and help customers focus on practical, valuable outcomes.
• Collaborate with Product and Engineering to identify gaps, product opportunities, technical constraints and reusable patterns.
• Review agent outputs for accuracy, usefulness, tone, compliance, consistency and customer experience.
• Support UAT, testing and launch readiness by making sure agent behaviour matches agreed requirements.
• Create clear documentation, including process maps, user stories, requirements, decision logs, test scenarios and customer-facing summaries.
• Help define what success looks like for each AI agent, including operational KPIs, customer experience measures and quality indicators.
• Keep up to date with practical developments in AI agents, LLMs, workflow automation, prompt design and AI governance.

What makes this role different from a traditional BA role

A traditional BA might document what a customer asks for. In this role, you’ll need to help customers work out what they actually need. You’ll need to understand when an AI agent is the right solution, when a process needs to change first, when automation could create risk, and when a human-in-the-loop approach is more appropriate.

You’ll be expected to think about:

• How an AI agent should behave in real customer scenarios.
• What information the agent needs to answer accurately.
• What the agent should not do.
• When the agent should escalate to a human.
• How to test whether the agent is performing well.
• How to design workflows that are useful, safe and maintainable.
• How to turn customer ambition into something deliverable.

This role requires strong BA fundamentals, but also curiosity, judgement and practical understanding of how AI can be applied in real business environments.

What we’re looking for

We’re looking for someone with solid experience in business analysis, solution delivery or customer-facing technology projects. You should be:

• Experienced in gathering, analysing and documenting business requirements.
• Confident running customer workshops and asking structured, thoughtful questions.
• Good at breaking down complex or messy processes into clear workflows.
• Able to distinguish between business needs, user needs, technical constraints and product gaps.
• Comfortable working with technical and non-technical stakeholders.
• Strong at writing clear documentation, user stories, acceptance criteria and process maps.
• Curious about AI, automation and how businesses can use agents to improve customer and operational outcomes.
• Practical and outcome-focused, with good judgement about what will actually work.
• Comfortable challenging assumptions and helping customers prioritise.
• Able to work closely with delivery, product and engineering teams.
• Strong at spotting ambiguity, risk, edge cases and gaps in requirements.
• Interested in customer experience, service design, digital transformation and operational improvement.
• Comfortable testing AI agent behaviour and reviewing outputs critically.
• Organised, reliable and able to manage multiple customer or project workstreams.

Useful skills or experience

You do not need all of these, but any of the following would be helpful:

• Experience as a Business Analyst, Product Analyst, Implementation Consultant, Solution Consultant or Digital Transformation Analyst.
• Experience in SaaS, customer service technology, contact centres, workflow automation or enterprise software.
• Exposure to AI tools such as ChatGPT, Claude, Gemini, Copilot or other AI platforms.
• Experience with conversational AI, chatbots, virtual agents or customer service automation.
• Experience creating process maps, user stories, acceptance criteria, test plans or solution documentation.
• Understanding of APIs, integrations, webhooks, CRM systems, ticketing systems or automation platforms.
• Experience working with Product and Engineering teams in an agile delivery environment.
• Experience supporting UAT, customer testing, implementation or go-live readiness.
• Familiarity with knowledge bases, FAQs, help centres, content design or service design.
• Awareness of AI risks such as hallucination, bias, unsafe responses, poor escalation design or unreliable knowledge sources.

You do not need to be:

• A machine learning engineer.
• A data scientist.
• A software developer.
• An AI researcher.
• A prompt engineering expert.
• A traditional BA who only writes requirements and avoids solution thinking.

We’re more interested in your ability to understand business problems, structure complexity, communicate clearly, work with customers, and help deliver practical AI agent solutions that create real value.

What success looks like

In your first few months, you’ll be able to:

• Understand how ServisBOT designs, builds and delivers AI agent solutions.
• Lead customer discovery sessions with support from senior team members.
• Produce clear workflow maps, requirements, agent behaviour definitions and acceptance criteria.
• Work with implementation colleagues to turn requirements into agent configurations, prompts, knowledge structures and test scenarios.
• Identify gaps, risks, edge cases and dependencies early.
• Support demos, playbacks and customer feedback sessions.
• Help customers understand what AI agents can and cannot realistically do.
• Contribute to better internal delivery patterns, reusable templates and best practices.

Over time, you’ll grow into someone who can take a customer problem from early discovery through to a clear AI solution design, working with the team to deliver agents that are useful, reliable, measurable and aligned to customer outcomes.

Why join us?

This is a chance to apply strong business analysis and solution design skills to one of the fastest-growing areas of technology: practical AI agents for real businesses. You’ll work on real customer problems, not theoretical AI experiments. You’ll help shape agents that support customer service, operations and business workflows, while learning from experienced colleagues across Customer Success, Product, Engineering, Architecture and Delivery.

You’ll also have the opportunity to help define what good AI business analysis looks like: how to capture requirements for AI agents, how to test agent behaviour, how to design safe and useful workflows, and how to help customers adopt AI in a practical way.