Solutions Engineer

DigitalGenius is the CX platform for e-commerce combining proprietary artificial intelligence with process automation to deliver incredible customer satisfaction. The company is growing rapidly and working with global e-commerce and retail players including G Star, ON, Selfridges, and Brooks Brothers.

Required:

• AI-first mindset; actively use AI tools and push to automate repetitive tasks
• Automation/workflow mindset; translate business requirements into reliable flows including edge cases
• Strong API and integration experience; comfortable with Postman, JSON, webhooks, auth, pagination, error handling, troubleshooting
• Hands-on Python experience writing and shipping code used by others
• Strong communication skills; explain technical concepts clearly to non-technical stakeholders
• Strong organization and project management skills managing multiple stakeholders and timelines

Preferred:

• Hands-on LLM experience including prompting, classification, guardrails, evaluation, and tooling like LangChain, LlamaIndex, OpenAI/Anthropic SDKs
• Low-code/workflow automation experience with tools like Zapier, Make, Workato, Tray.io, n8n, Salesforce Flow, ServiceNow, Power Automate, Retool
• E-commerce/OMS exposure especially Shopify
• Experience with customer service platforms such as Zendesk, Salesforce Service Cloud
• SaaS delivery background in implementations, solutions, or technical support in customer-facing environments

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 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 for customers and internally
• Contribute reusable assets, documentation, prompts, evaluation sets, and internal best practices
• Use AI to automate own work: build internal tools, scripts, and agents to improve team efficiency