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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Agent Engineer - **Company:** Digital Waffle - **Location:** Birmingham, UK - **Experience:** Experienced - **Salary:** £40,000.0 - £55,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Amazon Web Services, Computer Vision, Microsoft Azure, Cloud Computing, Continuous Integration, Python (Programming Language), Commercial Software, Large Language Models, Prompt Engineering, Front End Software Development, Virtual Agents, Software Version Control, Data Pipelines, Api Management - **Published:** July 31, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5821433067 ## About the Role * 3+ years commercial software engineering experience with strong Python * Built and shipped at least one LLM-powered feature or agent into production and operated it afterwards (real, used side projects count) * Practical grasp of the agent toolkit: function and tool calling, RAG, vector databases, structured output, prompt engineering and context management * Comfortable with at least one agent framework or SDK, with an understanding of why the abstractions exist rather than blind loyalty to a specific one * Solid API and integration experience, since much of this role is plumbing agents into systems that were not designed for them * Cloud deployment experience (AWS, GCP or Azure) and standard engineering hygiene: version control, testing, CI/CD * Able to talk to non-technical colleagues about what an agent can and cannot reliably do, and confident enough to push back when a request is a bad fit Nice to have: * Background in media, publishing, broadcast or content licensing * Multimodal work: image or video understanding, embeddings, automated tagging or computer vision * Experience building evals or LLM observability tooling * Workflow or pipeline orchestration at volume * Front-end capability for internal tools so users can see and steer what the agents are doing This role would suit an engineer who wants genuine greenfield ownership of an agent platform, a varied problem space spanning editorial, rights, archive and commercial, and short feedback loops with the people whose work the agents actually change. ## Description * Design, build and ship production LLM agents against real editorial, rights, archive and commercial workflows, from scoping through to deployment and monitoring * Build the shared platform underneath the agents including orchestration, tool and API integrations, retrieval, prompt management, evaluation and observability * Integrate agents with existing systems including the archive, submission portal, clips platform and internal editorial tooling * Work directly with editorial, research and commercial teams to identify the workflows worth automating and define what 'good enough to trust' looks like for each * Build evaluation and guardrails so agent output quality is measurable rather than anecdotal, with human review at the right points * Own cost and latency, keeping model spend proportionate to the work being replaced * Document and hand over so the platform is not a single-person dependency * Keep an eye on the tooling landscape and make pragmatic build-versus-buy calls ## Related Videos - [Guiding Agentic AI with Vue](https://www.wearedevelopers.com/videos/2033-guiding-agentic-ai-with-vue) - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) - [From APIs to MCP: Enterprise Governance, Registry, and Controls](https://www.wearedevelopers.com/videos/100336-from-apis-to-mcp-enterprise-governance-registry-and-controls) - [On a Secret Mission: Developing AI Agents](https://www.wearedevelopers.com/videos/1510-on-a-secret-mission-developing-ai-agents) - [AI in Leadership: How Technology is Reshaping Executive Roles](https://www.wearedevelopers.com/videos/1705-ai-in-leadership-how-technology-is-reshaping-executive-roles) - [When Should You Use an Agent? Architectural Trade-offs in Agentic Systems](https://www.wearedevelopers.com/videos/100109-when-should-you-use-an-agent-architectural-trade-offs-in-agentic-systems) ## Related Articles - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [A 5-Step Open-Source Setup for Agentic Engineering](https://www.wearedevelopers.com/magazine/738-a-5-step-open-source-setup-for-agentic-engineering) - [Never delegate the understanding](https://www.wearedevelopers.com/magazine/749-never-delegate-the-understanding) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [The Overflow: AI and Agentic Coding](https://www.wearedevelopers.com/magazine/721-the-overflow-ai-and-agentic-coding)