Senior Solutions Engineer (AI Systems)

• Translate ambiguous, real-world problems into clear technical designs and working systems
• Design, build, and deploy AI agents that integrate with customer platforms and data
• Own solutions end-to-end, including deployment, reliability, performance, and iteration
• Test solutions with real data, measure impact, and continuously improve outcomes
• Collaborate closely with Product and Engineering teams to deliver scalable, high-quality solutions

Own end-to-end AI solutions with real enterprise impactWork hands-on at the intersection of AI, systems, and customers

A successful candidate should have:

• A degree in Computer Science, Engineering, or a related field.
• Proficiency in software development, integration, and deployment.
• Ability to communicate technical concepts effectively to diverse audiences.
• A proactive approach to learning and adapting to new challenges.
• 5+ years' experience in software engineering, solutions engineering, or similar technical roles
• Strong foundations in software design, system architecture, and problem-solving
• Proven experience working across systems, APIs, integrations, and data flows
• Comfortable engaging directly with customers and owning open-ended technical challenges
• Clear communicator with a strong sense of ownership and accountability
• Strong interest in building AI-powered systems that work in real-world environments

Nice to have:

• Background in forward-deployed, customer-facing, or solutions-oriented engineering roles
• Exposure to AI agents, automation platforms, or conversational systems
• Experience operating, monitoring, and improving production systems

Our client is a fast-growing, product-led AI company working closely with enterprise organisations to embed intelligent systems into critical workflows. They specialise in deploying practical, production-grade AI that delivers measurable business outcomes.

• Opportunity to work on high-impact AI deployments with real enterprise customers
• High ownership role with autonomy from problem definition through to production
• Collaborative culture focused on learning, experimentation, and continuous improvement
• Exposure to cutting-edge AI use cases in real operational environments