AI Solution Architect

• Lead customer-facing Frontier AI projects, owning solutions end to end and guiding Forward Deployed Engineers in delivery.
• Work with customers and senior stakeholders to understand business problems and desired outcomes, and agree architectural principles and strategic direction.
• Oversee deployment, configuration, and integration of Actonomy products in customer environments, resolving technical challenges during rollout.
• Provide technical direction, support, and line management to Forward Deployed Engineers, helping them make sound decisions and develop.
• Gather user feedback and translate customer needs into product improvements in partnership with Product and Engineering teams.
• Create reusable deployment patterns and implementation assets to improve the speed and quality of future engagements.
• Support customer adoption and value-realization activities so customers gain lasting value from AI in their day-to-day work.
• Stay current with developments in AI, Microsoft technologies, and the Actonomy platform, and share knowledge with the team and customers.
• Work with senior stakeholders on architectural principles and strategic direction, develop customer relationships, and support account management.
• Advise on new AI technologies and approaches, and help colleagues learn, develop, and grow.

Technologies:

• Agentic AI
• AI
• Architect
• Azure
• Cloud
• Support
• PaaS
• Python
• RAG
• React

More:

We are Kainos, where we work together to transform digital services, deliver Workday solutions, and advance technology. Our people-first culture values ideas, supports growth, and brings together a diverse, collaborative team. Within Kainos, Actonomy develops innovative AI products and agentic solutions on the Azure stack, combining deep technical expertise with a focus on solving real problems and improving peoples working lives. We encourage continuous learning, collaboration, and doing the right thing, and are committed to diversity, equity, inclusion, and an accessible recruitment process. This is a manager-level AI Solution Architect role in our AI Engineering job family.

• Proven experience leading delivery of production AI solutions across challenges of varying size and complexity.
• Experience serving as technical lead on customer-facing projects, ideally involving software products or platforms deployed in customer environments.
• Significant hands-on experience with Python and public cloud platforms, particularly Azure, including SaaS and PaaS offerings.
• Hands-on experience building and deploying modern AI solutions, including large language models and agentic AI (prompt engineering, RAG, tool and function calling, and orchestration) on the Microsoft AI stack, such as Azure OpenAI, Azure AI Foundry, and Azure AI services.
• Proven technical ownership of an AI product or software project, including architecture, estimation, product planning, and user story or requirements creation.
• Ability to understand whole-solution architecture and communicate and negotiate it with senior and C-level stakeholders, including the commercial implications of design decisions.
• Ability to explain AI designs clearly to non-engineers in conversations, documentation, and presentations.
• Comfort working directly with customers and users, developing relationships, and supporting account management.
• Experience integrating products or solutions with customer systems and data sources, and resolving technical issues during implementation and rollout.
• Ability to prioritize across multiple major projects, particularly when working to deadlines.
• Demonstrated ability to manage, mentor, coach, and develop team members and the wider community, including managing a small number of staff.
• Desirable: Experience with React or similar technologies.
• Desirable: Familiarity with the Microsoft agent ecosystem.
• Desirable: Experience creating reusable deployment patterns and implementation assets.
• Desirable: Experience in consulting, customer-facing, or delivery roles.
• Desirable: Awareness of responsible AI and AI evaluation practices.
• Desirable: Active participation in technology communities and knowledge sharing, internally and externally.
• We expect our people to demonstrate our values: determination, honesty, respect, creativity, and cooperation.