At a Glance
- Tasks: Lead AI delivery programs and design multi-agent systems for global clients.
- Company: Cutting-edge tech firm focused on AI innovation and client success.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Join a dynamic team that values mentorship and continuous learning.
- Why this job: Shape the future of AI while working on impactful projects with industry leaders.
- Qualifications: Experience in deploying agent-based systems and strong coding skills in Python/TypeScript.
The predicted salary is between 80000 - 100000 € per year.
This is not a slide-making or prompt-engineering role. We are looking for someone who has built multi-agent AI systems that run in production - not demos, not pilots that died after a sprint. You will anchor AI delivery programs end-to-end, work directly with global clients, and stay sharp on a field that changes every few weeks. You will report into and replicate the function of a senior AI delivery leader - which means you need both the depth to architect solutions and the presence to walk a CXO through what you built and why it works.
Delivery & Architecture
- Own end-to-end delivery of AI-native programs - from architecture through production deployment
- Design and build multi-agent orchestration systems using LangChain, LangGraph, CrewAI, or equivalent
- Integrate agent systems with enterprise surfaces: APIs, ERPs, CRMs, data platforms - not toy datasets
- Define agent topology: tool routing, memory strategy, state machines, fallback handling
Agentic Coding & Development
- Run agentic coding workflows using Claude Code, Cursor, OpenAI Codex, or equivalent CLI tools
- Lead projects where AI writes significant portions of the codebase - and you guide, review, and ship it
- Work with CLAUDE.md, shared context frameworks, and multi-session agent setups for team use
- Debug non-deterministic agent outputs systematically - not by gut feel
Client & Stakeholder Engagement
- Translate business problems into agent architectures for global CXO-level stakeholders
- Run discovery workshops, solution reviews, and delivery cadences with client teams
- Prepare and present technical proposals, POC plans, and roadmaps - own the story end-to-end
Team & Practice
- Mentor junior AI engineers; raise AI engineering quality across the delivery team
- Stay current: evaluate new models, frameworks, and tooling before the hype catches up
- Contribute to internal knowledge bases, reusable frameworks, and accelerators
Skills
- Agent Orchestration: LangChain, LangGraph, CrewAI - not just conceptual
- Agentic Coding Tools: Claude Code CLI, Cursor, OpenAI Codex, Copilot
- RAG & Vector Stores: Chroma, Weaviate, Pinecone - knows where RAG breaks
- LLM APIs & SDKs: Anthropic, OpenAI, Gemini - prompt design, tool use
- Python / TypeScript: Primary languages for agent + backend development
- LangSmith / Observability: Tracing, evaluation, debugging agent runs
- Cloud Platforms: Azure, AWS, GCP (at least one) - deployment, infra, managed services
- API & System Integration: REST, gRPC, Kafka - enterprise integration patterns
- MCP / Shared Context: Model Context Protocol, CLAUDE.md, Beads
- Agent Evaluation: Testing non-deterministic outputs, guardrails, evals
- CI/CD & DevOps: Git, containers, pipelines - agents need to ship
- Client Communication: Can present architecture to a CXO without jargon
What You Must Have Actually Done
- Deployed 2–3 agent-based systems in production - stateful, multi-step, real users
- Used LangGraph for multi-agent orchestration with memory, tool routing, and state management
- Built projects where AI (Claude Code, Codex, Cursor) wrote significant portions of the code
- Implemented RAG pipelines end-to-end - chunking, embedding, retrieval, re-ranking, evaluation
- Integrated agents with real enterprise APIs - not just OpenAI playground or sample data
- Debugged a production agent failure - and fixed it without blaming the model
- Can articulate when NOT to use agents - that is how we know you have built things
- Experience with Claude Code CLI in team environments (CLAUDE.md, shared context, multi-session flows)
- Familiarity with LangSmith for agent tracing, evaluation pipelines, and debugging at scale
- Has shipped something using MCP (Model Context Protocol) or similar shared-context tooling
- QA/testing mindset for agents - systematic evaluation of non-deterministic outputs
- Background in IT services or consulting - managing client expectations while building
- Experience with SLMs, fine-tuning, or on-device/edge agent deployment
Digital Customer Experience Architect in London employer: Response Informatics
As a Digital Customer Experience Architect, you will thrive in an innovative environment that champions cutting-edge AI solutions and fosters a culture of continuous learning and collaboration. Our commitment to employee growth is evident through mentorship opportunities and access to the latest technologies, ensuring you stay at the forefront of the rapidly evolving AI landscape. Located in a vibrant tech hub, we offer a dynamic workplace where your contributions directly impact global clients, making this an exceptional place for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Digital Customer Experience Architect in London
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the industry. Attend meetups, webinars, or conferences related to AI and customer experience. You never know who might be looking for someone just like you!
✨Tip Number 2
Show off your skills! Create a portfolio that highlights your past projects, especially those involving multi-agent systems. Make sure to include real-world applications and outcomes to impress potential employers.
✨Tip Number 3
Practice your pitch! Be ready to explain your projects and how they solve business problems. Tailor your message to resonate with CXO-level stakeholders, showcasing your ability to communicate complex ideas simply.
✨Tip Number 4
Apply through our website! We’re always on the lookout for talent like yours. Don’t just send your CV; make sure to follow up and express your enthusiasm for the role. It shows initiative and can set you apart from the crowd.
We think you need these skills to ace Digital Customer Experience Architect in London
Some tips for your application 🫡
Show Your Real Experience:When you're writing your application, make sure to highlight the actual projects you've shipped. We want to see what you've done in the real world, not just what you know. Talk about those multi-agent systems you've built and how they’ve made an impact.
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, especially when it comes to complex topics like AI architecture. Use simple language to explain your experience and avoid jargon where possible, so we can easily understand your expertise.
Tailor Your Application:Make sure to customise your application for this role. Highlight your experience with tools like LangChain or Claude Code, and explain how you've used them in production. This shows us that you’re not just a fit for the role, but that you really get what we’re looking for.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures it gets into the right hands. Plus, it gives you a chance to explore more about us and what we do!
How to prepare for a job interview at Response Informatics
✨Know Your Stuff
Make sure you can talk in detail about the multi-agent AI systems you've built. Be ready to discuss specific projects where you've deployed these systems in production, not just in theory. Highlight your experience with tools like LangChain and Claude Code, and be prepared to explain how you integrated them with enterprise APIs.
✨Showcase Your Problem-Solving Skills
During the interview, focus on how you've translated complex business problems into effective agent architectures. Prepare examples of discovery workshops or solution reviews you've led, and be ready to discuss how you engaged with CXO-level stakeholders to present your solutions clearly and without jargon.
✨Demonstrate Your Technical Acumen
Be prepared to dive deep into the technical aspects of your work. Discuss your experience with debugging non-deterministic outputs and how you've systematically evaluated agent performance. Familiarise yourself with the latest models and frameworks, as staying current is crucial in this fast-evolving field.
✨Mentorship and Team Collaboration
Highlight any experience you have mentoring junior engineers or improving team practices. Talk about how you've contributed to internal knowledge bases or reusable frameworks. This shows that you're not just a lone wolf but someone who values collaboration and elevates the entire team's capabilities.
