AI agents & production engineering:

• Design, build and deploy AI agents into live client environments with real users and real business data;
• Build the infrastructure around agents, including triggers, queues, error handling, retries, fallbacks and monitoring;
• Define the access and infrastructure requirements for each solution, including credentials, permissions, data access, rate limits, service accounts and audit trails;
• Design appropriate human-in-the-loop processes where full automation is not suitable.

Agentic AI & automation:

• Build solutions using different agent and automation frameworks such as n8n, Make, Zapier, OpenAI Agents SDK, LangGraph, Claude Agent SDK & Skills, MCP servers or custom orchestration;
• Select the right framework and architecture based on the business problem rather than defaulting to a single technology;
• Integrate AI agents with external APIs, business systems and data sources;
• Turn successful one-off client implementations into reusable patterns and components.

Client discovery & solution design:

• Work directly with Operations, Sales, Support, Finance and other client teams to understand existing workflows and identify automation opportunities;
• Determine which processes are worth automating and where AI agents can deliver measurable business value;
• Translate non-technical business requirements into clear, buildable technical specifications;
• Explain technical decisions clearly to both engineering and non-technical stakeholders.

Documentation & continuous improvement:

• Document solutions and conduct handover sessions so client and internal teams can independently maintain what has been built;
• Help establish reusable engineering standards and processes for AI agent and automation development;
• Automate internal workflows and identify opportunities to improve how the company itself uses AI.

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• Strong software engineering fundamentals with hands-on experience in Python or TypeScript;
• Demonstrated experience building and deploying AI agents / agentic workflows in production, not only prototypes or sandbox projects;
• Hands-on experience with several agent or automation technologies such as n8n, Make, Zapier, OpenAI Agents SDK, LangGraph, Claude Agent SDK & Skills, MCP servers or custom orchestration;
• Confident working with APIs, integrations and webhooks;
• Comfortable with production engineering topics including authentication, scopes, secrets management, logging, monitoring, cost control and API limitations;
• Enough infrastructure knowledge to independently deploy and maintain the solutions you build;
• Able to demonstrate 2–3 AI agents you have built and deployed with measurable business outcomes such as hours saved, reduced error rates, improved cycle times or revenue impact;
• Strong client-facing and discovery skills with the ability to communicate effectively with non-technical stakeholders and turn business problems into technical solutions;
• Advanced English level;
• Pragmatic engineering mindset: able to choose a simple, reliable solution over unnecessary technical complexity.

• Experience with AI evals, observability or agent monitoring;
• Experience with RAG and vector databases;
• Frontend development experience sufficient to build usable interfaces around AI solutions;
• Experience with multi-agent orchestration;
• Security, data protection or compliance experience;
• Previous experience in an agency or consultancy environment, working across multiple client projects;
• Direct Selling industry experience is a plus, but not required.

• The chance to join a fast-growing AI consultancy at the point it's defining a category, with real client exposure from day one;
• A permanent, fully remote role with a basic salary and the potential to participate in the share option scheme;
• A seat at the table on how we evolve our methodology, our tooling and the way we work with clients. We want you shaping the playbook, not just following it.