About AFS Advanced Field Solutions Ltd (AFS) is an established software company building field-service management products used by organisations across Ireland and the UK. Our platforms contain approximately four million historical service records. We are using this operational data to develop practical AI products, including voice agents, diagnostic assistants, intelligent reporting, knowledge retrieval, workflow automation and natural-language access to business data. This is an opportunity to build production AI systems around real products, customers and operational data—not purely experimental or academic projects. The role We are looking for an experienced Applied AI Product Engineer with strong Python foundations and demonstrable experience taking AI or LLM-based products into production. You will be the senior technical owner of our applied-AI programme, responsible for taking products from business problem and feasibility analysis through architecture, implementation, evaluation, deployment and ongoing improvement. This is not a research, prompt-engineering or basic API-integration role. We need someone who can independently analyse an ambiguous business problem, challenge assumptions, identify risks, define acceptance criteria and deliver a reliable production outcome. We particularly value engineers who surface problems and bad news early, communicate clearly and take personal responsibility for whether the finished product genuinely works. What you will work on
• AI voice agents for field-service workflows.
• Autonomous scheduling and dispatch workflows.
• Retrieval-augmented generation using company and customer knowledge.
• Tool-calling and agentic systems connected to APIs and databases.
• Natural-language querying of structured operational data.
• Diagnostic assistants using historical service cases and technical documentation.
• Automated onboarding, reporting and business-process workflows.
• Evaluation systems for accuracy, faithfulness, reliability and regression.
• Monitoring latency, token usage, cost and production failures.
• Python APIs and services supporting AI products.
• Deployment and operation of secure, tenant-aware AI services. Responsibilities
• Analyse business problems and determine whether AI is the appropriate solution.
• Define technical architecture, assumptions, risks and acceptance criteria before development begins.
• Build and deploy complete AI product workflows rather than isolated demonstrations.
• Integrate AI services with existing databases, APIs, scheduling and operational systems.
• Establish automated evaluation, testing,



monitoring and regression controls.
• Identify flawed assumptions and recommend simpler or more reliable alternatives.
• Diagnose failures, complete root-cause analysis and implement corrective actions.
• Communicate technical risks, delays and bad news early and clearly.
• Maintain security, tenant isolation, permissions, logging and data protection.
• Support controlled customer pilots and convert successful pilots into production services.
• Help establish engineering standards and provide technical guidance to other developers. Essential experience
• At least five years of substantial commercial software-development experience, including strong Python development.
• Hands-on experience owning an AI or LLM product used by real customers, employees or production users.
• Experience taking a product from initial architecture through deployment and operational support.
• Experience with LLM APIs, RAG, tool calling, agents and structured model outputs.
• Production API development using FastAPI, Flask, Django or an equivalent Python framework.
• Strong SQL and relational-database experience, preferably PostgreSQL.
• Docker and practical cloud-deployment experience.
• Experience with automated testing, monitoring, logging, observability and failure handling.
• Strong debugging, root-cause analysis and incident-management skills.
• Ability to connect technical work to a measurable business outcome.
• Ability to challenge requirements, identify missing analysis and recommend better alternatives.
• Ability to explain precisely what you personally designed, coded and delivered.
• Strong working English and clear technical communication. Highly desirable
• LangChain, LangGraph, LlamaIndex or equivalent frameworks.
• Vector databases and embedding-based retrieval.
• AI evaluation tools and observability platforms.
• Prompt-injection protection and AI security controls.
• Asynchronous Python and scalable production API design.
• Azure, AWS or Google Cloud.
• Voice-agent, telephony or speech-system development.
• CI/CD, infrastructure automation and automated deployment.
• Experience with multi-tenant SaaS or operational business systems.




• Experience integrating AI with scheduling, workflow or field-service products.
• Technical leadership or mentoring experience. Evidence we will ask for Applicants should be prepared to discuss an AI system they personally helped take into production, including:
• The business problem it solved.
• Their individual contribution.
• Who used the system.
• How it was architected and deployed.
• How accuracy and reliability were evaluated.
• How hallucinations, failures, latency and cost were managed.
• A significant production problem and its root cause.
• How the problem was communicated to management or customers.
• An occasion when they challenged the original requirement or advised against building the requested solution.
• Any measurable result achieved. Finalists may be invited to complete a paid practical assessment based on a realistic AI product scenario. The assessment will evaluate analysis, judgement, testing and communication as well as code. Please do not apply if your AI experience consists mainly of coursework, personal experimentation, prompt writing or basic integration with an AI API without production responsibility. Initial priorities During the first 90 days, the successful candidate will be expected to:
• Review our current AI products and DAVE voice-agent architecture.
• Identify technical, product, security and data-quality risks.
• Deliver a working DAVE and UK Field Service workflow using realistic operational scenarios.
• Establish automated evaluation and regression testing.
• Implement production monitoring for accuracy, failures, latency and cost.
• Support a controlled customer pilot and report clearly on its results. Working arrangements This position is based in our Fuengirola office five days per week. It is not a remote or hybrid position. Applicants must already have unrestricted permission to work in Spain. AFS cannot provide visa sponsorship for this vacancy. Compensation will reflect the successful candidate’s demonstrated experience, technical judgement and record of owning production AI products.

What we offer
• Technical ownership of meaningful, practical AI products.
• Access to substantial real-world operational data.
• Direct involvement in product and architectural decisions.
• Close collaboration with company leadership, customers and developers.
• The opportunity to take AI products from concept into live customer use.
• The stability and credibility of an established software company combined with an ambitious AI programme.

📌 Applied AI Product Engineer (Fuengirola)
🏢 Advanced Field Solutions
📍 Fuengirola