System Engineer in Creative Studio

Purpose of the Role

The Systems Engineer will build, maintain, and scale the technical infrastructure that powers Kearney Creative Studio's internal products and workflows. Working under the architectural direction of the AI Creative Director, this role translates system designs into production-grade code, ensures reliability across live environments, and extends platform capabilities as the Studio's portfolio of tools and services grows.

This is a hands-on engineering role. The successful candidate will operate within an established technical architecture, implementing features, resolving issues, and maintaining the health of interconnected systems. Projects and priorities will shift as the Studio identifies new bottlenecks and opportunities; the role requires someone comfortable moving between different problem spaces and codebases.

The Studio's systems include AI-powered workflows alongside traditional automation. You don't need to be an AI specialist or come from an AI-first background, but we do need someone who's built at least one LLM-enabled workflow themselves and understands how the pieces fit together. If you have strong engineering fundamentals, hands-on LLM workflow experience, and curiosity about where AI fits into production systems, we'll bring you up to speed on the architectural patterns specific to our stack.

The initial contract will be for 1 year, with the possibility of extension depending on business needs.

Work can be performed from our London or Prague office, or hybrid.

Right to Work

Candidates must hold existing right to work in either the United Kingdom or the Czech Republic. Visa sponsorship is not available for this role.

Tools & Stack

You'll be working across the following stack day-to-day:

• Orchestration: n8n (self-hosted on Azure)
• AI: Claude API, OpenAI API, LangChain, LangGraph for agent workflows
• Cloud: Microsoft Azure (Container Apps, Functions, PostgreSQL with pgvector, Blob Storage)
• Microsoft estate: SharePoint, Microsoft Graph API, Teams integrations
• Languages: Python (FastAPI primarily), JavaScript / TypeScript
• Other: Docker, Git, Azure DevOps for CI/CD, Linux

First 6 Months

To give a sense of what success looks like, in your first six months you would expect to be:

• Shipping production automation workflows used by internal teams across the Studio.
• Taking ownership of the n8n orchestration layer, including monitoring, error recovery, and operational discipline.
• Extending Microsoft Graph and SharePoint integrations across existing AI-enabled systems.
• Building out documentation, runbooks, and handover materials so that systems can be understood and supported beyond the Studio.

Key Responsibilities

Build and Maintain Automation Systems

• Develop, test, and deploy automation workflows and integrations within the architectural direction set by the AI Creative Director.
• Implement API connections between internal platforms, cloud services, and third-party tools.
• Write and maintain webhook handlers, scheduled jobs, and error-handling logic to ensure system reliability.
• Monitor system health, diagnose failures, and implement fixes with minimal downtime.

Platform and Infrastructure Support

• Manage and extend cloud-hosted services, including deployment pipelines, environment configuration, and access controls.
• Maintain database and storage layers for data persistence, retrieval, and search operations.
• Support messaging and notification integrations across internal communication platforms.
• Ensure all systems operate within Kearney's governance framework, maintaining audit trails and compliance documentation.

API Development and Integration

• Build and maintain API connections (REST, GraphQL) to internal and external platforms.
• Implement authentication flows (OAuth 2.0, SSO, API key management) across integrations.
• Develop data transformation and validation layers to ensure clean data flow between systems.

Document and File Processing

• Build and maintain automated pipelines for document generation and manipulation across common enterprise formats.
• Implement file handling workflows including upload, retrieval, versioning, and metadata management.

Cross-functional Engineering Support

• Provide engineering support to other teams and functions as required, particularly where the Studio's technical stack intersects with wider platform builds.
• Collaborate with internal engineering and IT teams on shared infrastructure projects.

Testing, Documentation, and Handover

• Write clear technical documentation for all systems, covering architecture decisions, configuration, and operational runbooks.
• Build and maintain test coverage for critical workflows.
• Contribute to internal knowledge bases so that systems can be understood and supported by the wider team.

Technical Requirements

Essential

• Strong proficiency in Python and JavaScript.
• Working knowledge of Microsoft Azure (Azure DevOps, Azure-hosted services, access controls).
• Hands-on experience building at least one LLM-enabled workflow involving tool use, retrieval, structured outputs, API calls, or human-in-the-loop review. We're flexible on the platform — n8n, LangChain, LangGraph, Make.com, Flowise, Microsoft Copilot Studio, or similar. What matters is that you've built a real workflow that solves a real problem.
• Experience building and consuming REST APIs.
• Experience with authentication and identity management (OAuth 2.0, SSO, service accounts).
• Governance-first mindset, comfortable working within enterprise compliance frameworks, building security into design rather than retrofitting it.
• Familiarity with relational databases and data storage patterns.
• Comfortable in Linux environments with CLI tooling.
• Version control (Git) and CI/CD pipeline experience.
• Strong debugging and problem-solving skills across distributed systems.

Desirable

• Experience with C# (useful for our Microsoft estate work, but we can support ramp-up).
• GraphQL API experience.
• Deeper AI/LLM application experience, including production RAG pipelines, vector store selection and tuning, agent evaluation, or prompt engineering at scale.
• Familiarity with document format manipulation (XML-based office formats, OOXML).
• Experience with messaging platform development (bots, notifications, webhooks).
• Experience working within enterprise governance and IT approval frameworks.

Candidate Profile

We are looking for someone with 3+ years of professional engineering experience, ideally with exposure to enterprise or agency environments where they have built and maintained systems that other teams depend on. A formal computer science degree is welcome but not required; what matters is demonstrable experience shipping and maintaining production systems.

Operating model: the AI Creative Director sets the technical architecture and priorities; you own implementation quality, reliability, documentation, and delivery. We want someone who can take a system design, build it cleanly, push back where they see a better implementation route, and own delivery end-to-end. This isn't a role where you'd design AI systems from scratch — it's one where you'd build, harden, and scale what's been designed.

The right person is methodical, takes pride in clean code and clear documentation, and is comfortable operating in a creative environment where requirements evolve and priorities shift. They understand that governance and reliability are not obstacles to speed but enablers of it.