Implementation & Solutions Lead

The opportunity
You’ll be the company’s first hire, working directly with both founders to take ownership of customer implementation and onboarding.
The company has 16 live customers and is building an AI-native merchandising and supply chain planning platform for growing consumer brands across fashion, homeware and consumer products.
These are businesses that have outgrown spreadsheets and need better ways to plan inventory, purchasing, forecasting and cash flow. Their ERP and WMS systems continue to handle transactions, while the platform provides the planning, modelling and reporting layer on top.
As the first implementation hire, you’ll take what the founders currently do themselves and turn it into a repeatable, scalable process.
You’ll work directly with customers, understand their data and planning requirements, build their models, configure the platform and help them get value from it.
The role
The role sits across data modelling, planning logic and customer implementation.
The hard part is being strong across all three.
1. Data modelling
You’ll take messy customer data and work out how the underlying business should be represented.
For example:
Understanding how products, variants, suppliers and purchase orders relate to one another
Deciding what the underlying tables and entities should be
Mapping customer spreadsheets into a structured model
Identifying missing, duplicated or inconsistent data
Making sure the final model accurately reflects how the customer's business operates
You don't need to be a database engineer, but you should naturally think in terms of entities, relationships, structures and dependencies.
2. Planning logic
You’ll work with the commercial and operational logic that sits on top of the data.
This includes areas such as:
Forecasting
Seasonality
Safety stock
Size and colour mix
Landed costs
Supplier purchasing
Purchase orders
Inventory
Cash flow
Margin and planning assumptions
You'll need to be comfortable questioning a number when it doesn't look right, tracing how a calculation was produced and explaining the outcome clearly.
3. Customer implementation
You'll work directly with customers to understand their requirements, guide them through the model and get them successfully live.
That means:
Running onboarding meetings
Explaining how the model works
Managing expectations
Handling pushback
Identifying workable solutions when the platform doesn't currently support something
Communicating product gaps clearly to the founders
Building trust with customers throughout implementation
You should be comfortable saying “we can't do that today” when necessary, while still finding a sensible workaround or next step.
AI is part of how you work
The company is AI-native.
Customers increasingly interact with the platform through Claude via its MCP, while the internal team uses tools such as Claude Code to build and configure solutions.
You won't be expected to write everything from scratch.
Instead, you'll use AI to accelerate your work directing it to build, modify, analyze and troubleshoot solutions, then checking the output carefully against the underlying data and business logic.
You should be comfortable:
Using AI tools for real work every week
Reading and editing code or configuration
Reviewing AI-generated output critically
Checking calculations and data rather than blindly trusting the result
Learning new AI tools quickly
Turning repeated work into reusable prompts, templates, automations or skills
You don't need to be a software engineer.
You do need to be technically curious and comfortable working with systems.
What the work actually looks like
Some examples of the work you'll handle:
A brand sends three spreadsheets of open purchase orders. You determine that the data needs a purchase-order header and purchase-order-line structure, link the lines to product variants and load the data into the platform.
A customer wants stock projected by colour as well as style. You determine what needs to change in the underlying model and use AI tools to help implement the change.
A buyer says the forecast looks too low for peak season. You trace the calculation, identify what is driving the result, explain it in plain English and recommend a solution.
A customer wants to move from a 26-week to a 52-week forecast. You compare the approaches against historical actuals, assess where accuracy improves or deteriorates and make a recommendation.
A customer asks for functionality the platform doesn't currently support. You explain this honestly, identify a practical workaround and communicate the product gap to the founders.
You notice you've completed the same mapping several times. Instead of repeating the work, you turn it into a template, automation or AI skill so the next onboarding is faster.
What you'll own
Customer implementation
Own customer onboarding from kick-off through to go-live
Work alongside the founders initially, gradually taking full ownership
Understand customer requirements and translate them into workable platform configurations
Manage implementation timelines and customer expectations
Ensure customers are successfully using the platform after go-live
Data modelling & configuration
Design customer data structures within the platform
Map, clean and validate customer data
Configure models using AI and the company's tooling
Investigate data inconsistencies and resolve issues
Ensure platform outputs tie back to source data
Planning & analysis
Work with forecasting, inventory, purchasing and supply-chain logic
Sanity-check calculations and assumptions
Analyse historical performance and backtesting
Understand how changes to assumptions affect outputs
Identify when numbers don't make commercial sense
Process improvement
Document what works and what doesn't
Build reusable templates, mapping guides and checks
Identify opportunities for automation
Continuously reduce implementation time and effort
Build the company's implementation playbook as the customer base grows
Product feedback
Identify recurring customer requirements and pain points
Translate implementation issues into clear product feedback
Help founders prioritise product improvements
Feed customer insight directly into the product roadmap
What success looks like in your first 90 days
By 90 days:
You've successfully run at least one customer onboarding end to end, with a founder reviewing rather than leading.
Implementation time is being measured against the current baseline and beginning to decrease.
At least one reusable template, automation or AI workflow is actively being used.
Customers you've onboarded are actively using the platform.
You have started contributing to a repeatable implementation playbook.
Who we're looking for
All three areas are essential
Being exceptionally strong in two but weak in the third is unlikely to work in this role.
1. You think in data structures
Given a spreadsheet, you can look beyond the columns and understand the underlying business entities and relationships.
For example, you understand that:
A purchase order has multiple lines, and each line relates to a particular product or product variant.
You've worked with structured data or systems before perhaps through:
Databases
SQL
Airtable
Notion
Low-code platforms
Planning systems
ERP/WMS systems
Ecommerce platforms
Internal business tools
Your spreadsheet experience should go beyond reporting. You should have experience designing or structuring data, not simply consuming reports.
2. You use AI tools for real work
You use AI tools regularly to solve real problems and accelerate your work.
You may have experience with tools such as:
Claude
ChatGPT
Claude Code
Cursor
Copilot
Other AI-assisted development or productivity tools
You're comfortable reading and editing code or configuration, even if you're not a software engineer.
More importantly, you understand that AI can be wrong. You validate its output against data, logic and business reality.
3. You're strong with customers
You can sit with a founder, buyer, planner or operations team and understand what they actually need.
You can:
Explain complex information simply
Present a recommendation confidently
Ask good questions
Challenge assumptions constructively
Handle difficult conversations calmly
Manage e

Work arrangement
Yes