Evaluate and recommend technology stacks — including AI platforms and development tooling — with clear rationale.
Support architecture reviews and ensure solutions align with enterprise standards and governance requirements.
Engineering Delivery
Work closely with engineering teams to translate architecture into working, production-quality systems.
Apply modern engineering practices: clean code, CI/CD pipelines, testing strategies, and observability.
Participate in code and design reviews, sharing architectural context and raising quality across the team.
Comfortable getting hands-on — contributing code and debugging when it matters most.
Rapid Prototyping & AI Innovation
Lead proof-of-concept builds to de-risk architecture decisions and validate solution approaches quickly.
Use AI-assisted development tools (coding copilots, LLM APIs, agent frameworks) to accelerate delivery and exploration.
Translate prototype learnings into well-structured, production-ready architectures and delivery plans.
Stay current with the fast-moving generative AI landscape and bring relevant ideas to client engagements.
Consulting & Stakeholder Engagement
Engage directly with business and technical stakeholders to understand requirements and shape practical solutions.
Support workshops, solution design sessions, and technical discovery activities.
Communicate architectural thinking clearly — adapting the level of detail for different audiences.
Contribute to proposals, assessments, and solutioning work as part of client engagements.
TECHNICAL CAPABILITIES
Architecture & Design
Enterprise Solution Architecture, Microservices, Event-Driven and API-first design
Cloud-native systems, distributed architectures, integration patterns
Security-by-design, scalability and resilience principles
Artificial Intelligence & Emerging Technology
Generative AI platforms and Large Language Models (LLMs)
AI agents, intelligent automation, and prompt engineering
AI-assisted development workflows and tooling
Engineering & Delivery
Modern software engineering, DevOps, CI/CD pipelines
Observability, reliability engineering, and testing strategies
Rapid prototyping and proof-of-concept development
Python, modern application frameworks, API-based architectures
WHAT SETS THIS ROLE APART
You'll work at the intersection of architecture, AI, and consulting — not siloed in one discipline.
Real exposure to generative AI in enterprise settings — not just theory, but hands-on delivery.
Mentorship and growth from senior technology and business leadership while owning meaningful pieces of complex client solutions.
A culture that values engineering quality, intellectual curiosity, and getting things built.
TOOLS & PLATFORMS
AI & Language Models
OpenAI API (GPT-4 and beyond) — prompt engineering, function calling, embeddings
Anthropic / Claude — enterprise AI integration, Claude API, responsible AI workflows
Data & Analytics
Databricks — unified data and AI platform, Delta Lake, MLflow, notebooks
Snowflake — cloud data warehousing, data sharing, and analytics at scale
Cloud & Infrastructure
Azure / AWS / GCP — cloud-native architectures, managed services, IAM, networking
Docker / containerised deployments, cloud-managed compute and serverless patterns
Development & Source Control
GitHub / Git — version control, branching strategies, pull request workflows, CI/CD integration
FastAPI / Python frameworks — API development, backend services, AI application scaffolding
EDUCATION
Bachelor's Degree in Computer Science, Software Engineering, or a related technical discipline — or equivalent practical experience.
We are dedicated to building a diverse, inclusive, and authentic workplace, so if you’re excited about this role but your experience doesn’t perfectly align with every qualification, we encourage you to apply anyway. You may be just the right candidate for this or other roles.
