Solutions Engineer

At DigitalGenius, we build AI that resolves e-commerce customer service end to end: order issues, carrier problems, returns, refunds and replacements, often before the customer notices anything is wrong. Our customers include some of the biggest names in retail including On, Rapha, Air Up, Holland & Barrett, AllSaints, Honeylove, and Clarins.

As a Solutions Engineer you are the technical owner of your clients' automation, and the person they talk to about it. You sit with a client's operations and engineering teams, decide and advise how their solution should work, build it, and stay accountable for it once it is live. If you want to be left alone to write code, this is the wrong job. Reporting to our Lead Solutions Engineer and working alongside Customer Success, your responsibilities will include:

• →Running scoping sessions with a client's operations and engineering teams, and working out what they actually need
• →Presenting your design, making the case for it, and steering clients away from approaches that will not hold up
• →Designing and building automation flows in the DigitalGenius platform for complex, high-volume use cases
• →Integrating the platform with the client's ecosystem (Shopify, Zendesk, Gorgias, Loop, OMS platforms, carriers) via APIs and webhooks
• →Building custom actions in Python where a use case needs one
• →Prompting, tuning and evaluating the LLM components that decide what the agent does
• →Troubleshooting behaviour across systems, data and AI, often live with the client
• →Reporting results back in a way a non-technical stakeholder can act on, and growing the account into new use cases
• →Taking what you see in real implementations back to Product, so the platform grows in the direction clients need

• 2+ years in a technical role working directly with external clients: solutions engineering, implementation, professional services, technical consulting, technical account management, or escalation-level technical support.
• Proven client-facing judgement. You can run a scoping call and explain a technical decision to a non-technical audience, push back on a request that will not work, and stay clear when something has broken in production.
• Strong understanding of APIs, JSON, webhooks, auth, pagination and rate limits, and the patience to find the gap between what documentation says and what an endpoint actually does.
• Python. You can write/understand and debug a script, read someone else's code, and explain your design choices and how you tested them.
• Hands-on experience building automations in a low-code or config-heavy tool: Zapier, Make, n8n, Workato, UiPath, Salesforce Flow, Power Automate, Retool, or a vendor's own platform.
• Daily use of AI tools in your own work, with a clear view of where they help and where they need correcting.
• Proven experience running several client projects at once against deadlines.

• LLM work: prompting, classification, guardrails, evaluation, OpenAI or Anthropic SDKs
• E-commerce and OMS, especially Shopify: orders, fulfilments, returns, refunds, webhooks
• Customer service platforms: Zendesk, Gorgias, Dixa, Salesforce Service Cloud
• SaaS post-sales delivery: implementations, professional services or solutions teams

We keep our process transparent and respectful of your time. Here's what to expect:

• Round 1 (30 mins): Intro call with our Lead Solutions Engineer.
• Round 2 (1 hour): Review of a take-home technical exercise with a panel (usually two people).
• Round 3 (30 mins): Conversation with our CTO and VP, Product Delivery & Support
• Round 4 (20 mins): Final chat with our CEO.