AKQA
Principal Engineer (Gen AI and MACH Architecture)
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Senior Principal Engineer (Technical Lead) – Generative AI & MACH Architectures
Location: London (Farringdon) Working Model: Hybrid Division: AKQA Tech London
About the Role
At AKQA, we blend art and science to craft immersive solutions that blend creativity with cutting-edge technology. We seek a senior architecture-led Principal Engineer (Technical Lead) to spearhead technical leadership, hands-on development, and enterprise-grade system design across MACH architectures and production-grade Generative AI.
This role sits between strategic design and execution, balancing 30-35% technical leadership (architecture, mentorship) with 65-70% hands-on delivery—you’ll own architectures from concept to production, write code, and mentor engineers while ensuring what ships reflects your leadership.
You will drive Design-to-Code workflows, embed Generative AI into production experiences, and deliver scalable, AI-powered solutions spanning retrieval pipelines, governance, cost optimisation, and operational reliability. Collaboration with Technical Managers, cross-functional squads, and global teams is core to this role.
Key Responsibilities
- Lead the technical design and build of enterprise-scale AI systems, including RAG, GraphRAG, agent orchestration, and relevance-engineered experiences within MACH frameworks.
- Ship production-ready AI capabilities—beyond prototypes—to emcarge, marketing, and experience platforms, ensuring reliability, cost-efficiency, and measurable business outcomes.
- Bridge design intent and engineering teams, applying Generative AI to accelerate Figma-to-code workflows and automate validation/quality checks.
- Advise on AI integration architectures across platforms like:
- Vercel AI SDK & Cloud
- GCP Vertex AI / Google Kubernetes Engine (GKE)
- AWS Bedrock / Azure OpenAI
- Cloud AI services (with preference for Vercel/GCP or parallel AWS/Azure experience)
- Optimise LLM retrieval, geo-sensitive content delivery, and AI workflows for cost, observability, and performance.
- Mentor engineers and guide squads through MACH principles (microservices, API-first, headless CMS, and cloud-native architectures).
- Shape engineering culture by advocating for automation, quality, and scalability—proposing improvements rooted in real-world production challenges.
- Collaborate with clients, stakeholders, and teams to translate technical ideas into business value, demystifying complexity effectively.
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Requirements
Generative AI & Intelligent Experience Architecture
✅ Three years+ experience shipping Generative AI—not limited to PoCs—into enterprise production environments.
- Architecture:
- Experience platforms for e.g., RAG, GraphRAG, agent orchestration, and relevance/evaluation pipelines.
- Implementation:
- Hands-on design with Vercel AI SDK/Cloud and agent cloud patterns.
- Data Engineering:
- Ingestion, embedding, indexing, and retrieval pipeline optimisations.
- Operations:
- AI cost modelling, governance frameworks, observability, and testing for production-grade systems.
- Practical Applications:
- AI-driven personalisation, campaign optimisation, and content generation with verifiable business impact.
Design Systems & Design-to-Code
✅ Advanced Design-to-Code thinking:
- Transform Figma systems into scalable, production-usable UIs/applications and experiences.
- Integrate Generative AI in design-to-code workflows—e.g., applying LLMs to accelerate builds, automate codegen, and ensure quality.
- Expertise with tools like Cursor, Claude AI, and Vercel v0 is a strong plus.
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Platform Architecture & Engineering
✅ 10+ years of hands-on experience in MACH-based enterprise platforms:
- Cloud-Native/Government/Efficient APIs (RESTful/GraphQL, contract-first design, gateways, and contracts across CMS/DXP stacks).
- Deep cloud expertise (GCP preferred, Vercel-first, with parity on AWS/Azure):
- Infrastructure design, security, observability, and CI/CD pipelines.
- IaC (Terraform, Pulumi), Kubernetes.
- Distributed systems & Event-Driven Architecture:
- Resilience, queues, async workflows, backoff/retry strategies.
- Backend Development:
- Python preferred; other languages (e.g., Go, Rust) plus.
- Frontend Literacy:
- Core HTML/CSS/JS + React, familiar with FWs like Angular/Vue.
- CMS/DXP/MarTech ecosystems (e.g., Contentful, Sanity, headless CMS).
- DevOps & CI/CD Feedback:
- GitHub Actions, Azure DevOps, GitLab CI, and automation frameworks.
Qualities & Characteristics
- Philosopher-Engineer: A "builder-first" mindset—architecture informed by production delivery.
- Engineering Culture Evangelism: Drive quality, security, and reliability—remove technical debt, simplify chaos.
- Technical Storyteller: Translate complex architectures for non-technical audiences while advocating for technical integrity.
- Concrete Pragmatism: Hands-on delivery beats abstract theory.
- LLM + Deep Tech Curiosity: Stay ahead of Design-to-AI workflow and macroeconomic trends.
Example Work in Generative AI
AKQA applies Generative AI globally: Examples:
- Google: Reimagining emotion in e-commerce via dynamic discoverability.
- Nike: AI to Next Done: fitness apps powered by generative insights.
- Netflix: Game engine to semantic curation—"It's What's Inside".
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