AI Solution Architect

Archer; United States; On-site; USD 180,000 - 240,000; Full time

Job summary

Archer in collaboration with Kainos seeks an experienced AI Solution Architect for Actonomy frontier projects. You will lead a team of Forward Deployed Engineers, delivering end-to-end AI solutions inside customer environments and guiding architectural decisions.

You’ll work with senior stakeholders, manage staff development, and drive product improvements based on real-world feedback, staying ahead in AI and Microsoft tech. Strong client engagement and cloud expertise are essential.

Qualifications

• Proven experience delivering production AI solutions for large or complex engagements.
• Experience leading customer-facing AI projects and teams.
• Strong Python development and cloud platform skills (Azure).
• Knowledge of large language models, RAG, and AI tooling.
• Ability to communicate architecture to senior stakeholders.

Responsibilities

• Lead Frontier AI projects as technical lead, guiding a team of engineers.
• Work directly with customers to understand problems and outcomes.
• Oversee deployment, configuration and integration of Actonomy’s products.
• Provide technical direction and line management to engineers.
• Translate customer feedback into product improvements.
• Create reusable deployment patterns and assets.
• Drive adoption and value realization of AI solutions.
• Stay current with AI developments and Microsoft technologies.

Skills

AI architecture

Leadership

Python

Azure cloud

Customer engagement

Tools

Azure OpenAI

Azure AI Foundry

Microsoft stack

Job description

Archer is collaborating with Kainos to connect them with exceptional professionals for this role.

As an AI Solution Architect in Actonomy, you’ll be the technical lead on our customer‑facing Frontier AI projects, responsible for the successful delivery of high quality AI solutions built on Actonomy’s products. You’ll lead a team of Forward Deployed Engineers working hands‑on inside customer environments to turn ambitious AI ideas into production reality. It’s a role that combines engineering, consulting and product thinking, so you’ll be as comfortable in front of a customer as you are in the code.

As a technical leader, you’ll work with senior stakeholders to agree architectural principles and strategic direction, develop customer relationships and account management, and feed what you learn on the ground back into our product direction. You’ll manage, coach and develop a small number of staff, with a focus on performance and career development, whilst advising on new technologies and approaches to AI and helping the people around you learn, develop and grow.

Your Key Responsibilities Will Include

• Leading Frontier AI projects – You’ll be the technical lead on customer engagements, owning the solution end to end and guiding a team of Forward Deployed Engineers to deliver it.


• Working directly with customers – You’ll work with customers and senior stakeholders to understand their business problems and desired outcomes, and agree architectural principles and strategic direction.


• Deploying and integrating – You’ll oversee the deployment, configuration and integration of Actonomy’s products within customer environments, and resolve the technical challenges that arise during rollout.


• Leading your team – You’ll provide technical direction, support and line management to a team of Forward Deployed Engineers, helping them make the right decisions and grow.


• Closing the product loop – You’ll gather user feedback and translate customer needs into product improvements, working closely with our Product and Engineering teams.


• Building reusable assets – You’ll create reusable deployment patterns and implementation assets that make each engagement faster and better than the last.


• Driving adoption and value‑realisation activities so customers get real, lasting value from AI in their day‑to‑day work.


• Staying at the frontier – You’ll stay current with developments in AI, Microsoft technologies and the Actonomy platform, and share that knowledge with your team and customers.

Minimum (essential) Requirements

• Proven experience leading the delivery of production AI solutions across different sizes and shapes of challenge (e.g. an AI service, a multi‑team programme, a customer platform deployment or a complex integration).


• Experience acting as the technical lead on customer‑facing projects, ideally deploying software products or platforms within 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 with modern AI, including large language models and agentic AI (prompt engineering, RAG, tool and function calling, orchestration), on the Microsoft AI stack such as Azure OpenAI, Azure AI Foundry and Azure AI services.


• Proven experience of technical ownership for an AI product or software project, including architecture, estimation, product planning and user story/requirement creation.


• Able to understand whole‑solution architecture and to communicate and negotiate it with senior and C‑level stakeholders, including the commercial implications of design decisions.


• Able to simplify and clearly communicate AI design in conversation, documentation and presentations to non‑engineers. Comfortable 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.


• Able to prioritise across multiple major projects, particularly when working to deadlines.


• A demonstrated ability in managing, mentoring, coaching and developing members of your team and the wider community, including managing a small number of staff.

DESIRABLE

• Experience with React or similar technologies.


• Familiarity with the Microsoft agent ecosystem.


• Experience creating reusable deployment patterns and implementation assets.


• Experience working in consulting, customer‑facing or delivery roles.


• Awareness of responsible AI and AI evaluation practices.


• Active participation in technology communities and knowledge sharing, internally and externally.