This is a high-impact, applied AI role — not a research position, not model-building. As an AI Operations Engineer, you will design, build, and deploy AI-powered tools and automated workflows that make Quantum Workplace's revenue and customer teams faster and more effective. You will partner directly with Sales, Customer Success, and Marketing to identify the highest-leverage problems, prototype solutions rapidly, and scale what works into reliable production systems.
You will sit at the intersection of software engineering and applied AI — translating real business problems into scalable, production-grade services. This is a foundational role in QW's strategy to embed AI across the business, which means high visibility, high autonomy, and a short feedback loop between what you build and the impact you can see.
Why This Role- You will be among the first to embed AI across the business — this is a foundational role with real strategic weight, not a support function
- Direct access to business stakeholders means a short feedback loop between what you build and the outcomes you drive
- High autonomy: prototype fast, ship what works, kill what does not
- A company with genuine conviction about AI as a business lever — not just a buzzword initiative
- Opportunity to shape how AI gets built and governed inside a growing SaaS company
What You'll Do:
- Partner with Sales, Customer Success, and Marketing to identify and prioritize high-leverage AI automation opportunities
- Design, build, and deploy AI-enabled services and agent-based workflows end-to-end
- Rapidly prototype solutions to validate value before committing to full production builds
- Implement multi-step AI workflows with tool usage, data retrieval, and external system integration
- Build and maintain API-driven backend services supporting AI-powered applications
- Create frontend components and user interfaces that support AI workflows
- Integrate AI systems with enterprise data platforms, CRM tools, and business systems
- Design testing strategies to ensure AI outputs are accurate, reliable, and safe for production
- Build observability, logging, and monitoring into AI services from the start
- Ensure solutions meet security, compliance, and governance standards
- Contribute to architectural reviews and help shape platform standards and best practices
What You'll Bring:
- 3+ years of professional software development or data science experience
- Proficiency in Python, C#, TypeScript, or similar languages used in AI and automation contexts
- Hands-on experience building AI-powered workflows or agent-based systems using LLM APIs (Claude, OpenAI, or similar)
- Proficiency with SQL and relational database design
- Experience building and consuming RESTful APIs
- Strong communication skills — you can translate technical work into terms that resonate with business stakeholders
- Experience with AI agent frameworks such as the Claude Agent SDK, Microsoft Agent Framework, or OpenAI Agents SDK
- Familiarity with low-code/no-code automation platforms (Zapier, n8n, Make)
- Experience integrating with CRM, marketing automation, or BI platforms (HubSpot, Salesforce, Marketo)
- Exposure to observability and monitoring tools (Datadog, New Relic, or similar)
- Experience with cloud platforms (Azure, AWS, GCP) and CI/CD pipeline practices
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