Solution Architect, Agentic Engineering

Define, own, and evolve the high-level technical architecture for internal and client platforms and shared services, ensuring systems are scalable, secure, observable, and production-ready.

Organizing, distributing and translating backlog requirements from Product, UX and other disciplines, into detailed spec driven requirements for Agents to implement.

Synthesize user stories, site maps, content strategy, components and design systems, brand strategy, etc, into specifications that coding Agents will implement.

Designing and implementing digital solutions that have proper SEO/GEO, accessibility, performance and content management integrations.

Integrations with key Composable platforms such as Contentful, Contentstack, Algolia, Cloudinary, etc.

Champion spec-driven development as a core practice to improve clarity, quality, and predictability across teams.

Design and guide layered and distributed architectures, ensuring sound use of queues, caching, APIs, and database schemas while using teams of coding agents.

Establish standards for creating and consuming RESTful APIs across services.

Coach engineers on effective agent design, prompt architecture, and decision modeling.

Translate business goals into agent capabilities and system-level behaviours.

Define when autonomy is appropriate vs. when human oversight is required.

Lead the design and implementation of AI-powered systems, including: LLM integrations (Gemini 3, Claude Opus, GPT-4.x/5.x); Vector stores and Retrieval-Augmented Generation (RAG) pipelines.

Set direction for agent observability, debugging, and reliability in production environments.

Embed AI coding agents (Copilot, Claude Code, etc.) into development workflows to improve velocity, quality, and developer experience.

Continuously evaluate and introduce new AI tools and techniques to accelerate delivery while maintaining enterprise standards.

Promote disciplined experimentation and learning around emerging AI capabilities.

Provide technical leadership for systems built on Google Cloud Platform (GCP).

Oversee infrastructure design and provisioning, with Terraform as a preferred approach.

Ensure systems meet expectations for reliability, scalability, and operational excellence.

Lead and mentor senior engineers and technical leads across multiple teams.

Foster a calm, supportive, and solution-oriented engineering culture.

Partner with Engineering Managers, Product, and Delivery leaders to align technical initiatives with organizational goals.

Manage dependencies and technical risks across concurrent initiatives.

Identify and mitigate technical, architectural, and delivery risks early.

Drive continuous improvement in how software is designed, built, tested, and operated, especially through AI-enabled practices.

Ensure systems and teams are prepared for long-term maintainability and evolution.