Architect AI-driven solutions. Design agents, integrations, and automation that change how engagements are delivered. Solutions should be reusable across accounts, not one-off scripts.
Lead delivery through GA. Own a solution end to end, architecture through build, until general availability and Professional Services delivery can run it independently. After GA, Delivery leads and you provide support.
Document solutions and processes. Document each solution so others can run, extend, or troubleshoot it without you. Documentation is part of the deliverable, not an afterthought.
Drive adoption and gather feedback. Support the internal and Professional Services communities who use what you build, and gather their feedback to confirm solutions meet real needs. Adoption determines impact.
Collaborate with architects and Delivery. Support fellow architects, and stay informed on Delivery and Product activity so solutions reflect field reality., Systems perspective. You can reason about an entire architecture, data, integrations, content, commerce, identity, and the seams between them. You've worked across more than one category: CMS, commerce, ERP, CRM, data platforms, integration, and identity. You see Professional Services delivery as a system that can be redesigned with AI.
Root-cause analysis. You identify the actual source of recurring delivery friction, not just its symptoms, and can demonstrate your reasoning.
Applied AI engineering. You have built and shipped production AI systems: agents, LLM-based workflows, and API integrations. You can design an approach and implement it yourself.
Problem definition under ambiguity. You can scope and design a solution from incomplete or conflicting requirements, make sound tradeoffs, and defend your approach under pressure.
Regional awareness. You understand the differences between EMEA and North America delivery, and design solutions for consistent execution across both., You deliver against the roadmap. UMP, MCP, and future initiatives progress from concept to general availability and adoption.
You turn challenges into solutions. You convert ambiguous problems into working solutions without waiting for a complete specification.
Your work improves how we deliver. Solutions you build measurably improve delivery: fewer manual steps, faster engagements, and faster time-to-value for customers.

Generative AI and agentic engineering. Experience with LLM integration: prompt engineering, RAG pipelines, vector stores, and an orchestration framework such as LangChain or LlamaIndex.
Cloud and MLOps. Working knowledge of a major cloud platform (AWS, Azure, or GCP), including containers, CI/CD, and model monitoring.
Production-grade programming. Proficiency in Python or a comparable language, sufficient to build and ship production systems.
Systems and integration design. Experience with distributed systems, API design, event-driven architecture, and third-party integrations.
Responsible AI and security. Understanding of bias mitigation, model risk, privacy, compliance, and core security practices: authentication, authorization, encryption, and secrets management.
Optimizely product knowledge. An advantage, not a requirement. It accelerates onboarding and collaboration with Delivery and Product.

2 Optimizely jobs in England & Wales