At DigitalGenius (DG), our mission is to make online shopping a seamless experience. We believe we can achieve this using conversational AI and deep integrations.

While most chatbots only cause frustration, we have built an e-commerce chatbot that actually works. It resolves customer issues end-to-end, detects carrier problems, performs investigations, issues return labels, refunds, and replacements — and does all of this proactively, often before the customer even notices the issue.

Some of the customers who have joined us on this mission: On, Holland & Barrett, Cozey, Caraway, MyTheresa, Clarins, Air Up, Universal Music Group, Huda Beauty.

We are a committed team of like-minded people who believe in the product we are building and the vision behind it. Each of us operates in our own bubble of autonomy and responsibility, but the magic happens when we collaborate and make all the pieces fit together. DG is for the passionate, the curious, and the overachievers. We thrive by exceeding expectations — not because we have to, but because we care.

About the role

A Solutions Engineer at DigitalGenius works in post-sales, partnering closely with Product and Customer Success Managers (CSMs) to design, implement, and optimize AI-driven customer service solutions for our clients. You are the technical owner of customer implementations, ensuring every solution is scalable, secure, high-performance, and aligned with both business goals and our platform's capabilities.

You'll spend your time turning messy real-world e-commerce problems into reliable AI-powered automations — designing flows, wiring up integrations, writing Python where the platform stops, prompting and evaluating LLMs, and continuously raising the bar on what our AI agents can resolve autonomously.

Key Responsibilities

Solution Design & Implementation

• Translate business requirements into scalable technical solutions on the DigitalGenius platform
• Configure workflows, AI agents, integrations, and automation logic for complex e-commerce use cases
• Design and implement APIs and third-party integrations (OMS, carriers, Helpdesk, etc.)
• Prompt, tune, and evaluate LLM-powered components — classifications, extractions, guardrails, and generative replies

Technical Ownership (Post-Sales)

• Lead new use case implementation projects
• Ensure timely, high-quality launches with measurable automation impact
• Troubleshoot complex technical challenges across systems, data, and AI behavior

Customer Collaboration

• Partner with CSMs to align technical delivery with customer outcomes and ROI
• Advise customers on best practices, scalability, AI strategy, and optimization
• Support strategic expansions, new channels, and advanced use cases

Product Partnership

• Provide structured feedback to Product based on what you see in real implementations
• Identify feature and AI capability gaps and contribute to roadmap discussions
• Participate in beta testing, model evaluations, and product validation initiatives

Optimization & Innovation

• Continuously improve automation performance, resolution rates, and AI accuracy
• Proactively identify opportunities for process improvements — both for customers and internally
• Contribute reusable assets, documentation, prompts, evaluation sets, and internal best practices
• Use AI to automate your own work: build internal tools, scripts, and agents that make the SE team faster and better

Requirements

Required

• AI-first mindset. You're genuinely excited about LLMs and applied AI. You actively use AI tools in your day-to-day work, you push to automate the repetitive parts of your own job, and you believe most manual work in our space will eventually be done by agents.
• Automation / workflow mindset. You can translate business requirements into reliable flows — including edge cases, data mapping, retries, and clear decision logic.
• Strong API + integration experience (building and debugging). Comfortable with Postman, JSON, webhooks, auth (tokens, headers, OAuth), pagination, error handling, and troubleshooting unexpected API behavior.
• Python. Hands-on experience writing and shipping Python used by others — integrations, automation scripts, services, or internal tools. You can explain your design choices and how you tested and debugged your code.
• Strong communication. You can explain technical concepts clearly to non-technical stakeholders, write clean notes and docs, and keep customers and internal teams aligned.
• Organization and project management. Strong organizational skills with the ability to manage workstreams, priorities, and timelines across multiple stakeholders and parallel implementations.

Preferred

• Hands-on LLM experience. Prompting, classification, guardrails, evaluation, and tooling like LangChain, LlamaIndex, OpenAI/Anthropic SDKs — bonus if applied in support automation or agentic workflows.
• Low-code / workflow automation experience. Zapier, Make, Workato, Tray.io, n8n, Salesforce Flow, ServiceNow, Power Automate, Retool — or a proven track record of learning config-heavy tools quickly.
• E-commerce / OMS exposure (especially Shopify). Orders, fulfillments, returns and refunds, customer data, tags and statuses, webhooks.
• Customer service platforms. Zendesk, Salesforce Service Cloud, or similar.
• SaaS delivery background. Implementations, solutions, or technical support in customer-facing environments.

Benefits

• Competitive Salary
• Generous vacation time (25 days) + Birthday off
• Environment to develop your skills without bureaucracy or red tape
• Monthly fitness stipend of $210 (Lifestyle wallet) from day 1
• Ongoing subscription to Mental Health Support Platform
• Paid Claude/Cursor subscription: because we want you using the best AI tools every day
• Learning budget to invest in courses, books, conferences, and certifications

Interview Process

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.