AR
Applied AI Engineer – LLM & Agentic Systems
Contract type
Ongoing
Work mode
Remote · Europe
Experience
Mid-level · 3+ years
Job description
An Applied AI Engineer role at a UK AI-native property management technology company, focused on designing, building and maintaining production-grade LLM-powered agents and multi-agent systems. The position is backend-engineering heavy and requires hands-on ownership of agentic AI systems running in production.
At a glance
- Employment
- Full-time · Employee or contractor
- Work mode
- Remote · Europe
- Languages
- English – fluent
- Pay
- EUR 100,000 – 150,000 / year
What you'll do
- Design, build, and maintain production-grade LLM-powered agents and multi-agent systems
- Develop agentic workflows involving task decomposition, tool calling, structured outputs, orchestration, and feedback loops
- Build reusable agent components, including memory, context management, and tool integrations
- Design scalable architectures connecting AI agents with backend services, databases, and business applications
- Establish architectural patterns that allow new AI workflows to be introduced efficiently
- Design and implement automated evaluation frameworks for AI agents
- Create evaluation datasets with measurable success criteria and pass thresholds
- Integrate agent evaluations into CI/CD pipelines and release processes
- Monitor and improve agent reliability, latency, accuracy, and operational costs
- Investigate hallucinations, incorrect tool calls, unexpected outputs, and production failures
- Develop observability, debugging, error-handling, and fallback mechanisms
- Collaborate with product managers, data engineers, and operational teams to identify automation opportunities
- Transform complex business processes into reliable AI-driven solutions
- Take ownership of features from architecture and development through deployment and production monitoring
- Use modern AI coding agents, such as Claude Code or Codex, to improve engineering productivity
- Contribute to technical decisions, engineering standards, and long-term platform scalability
What we're looking for
- 3+ years of professional software engineering experience, with strong backend development expertise
- Hands-on experience with TypeScript/Node.js, or strong Python backend experience with willingness to work in a TypeScript-first environment
- Experience designing APIs, integrating databases, and building scalable production applications
- Strong understanding of software architecture, testing, CI/CD, and production reliability
- Bachelor's degree in Computer Science or a related technical field
- Proven experience personally building and deploying LLM-powered agents or agentic systems used by real users in production
- Hands-on experience with agent orchestration, tool calling, structured outputs, context management, and feedback loops
- Ability to explain the complete architecture of an AI system you developed, including your individual technical contributions
- Experience handling real production challenges involving latency, cost, reliability, hallucinations, and failure recovery
- Practical experience building agent evaluations, including evaluation datasets, measurable success thresholds, and automated testing or release gates
- Understanding of when to use LLMs, deterministic software, multiple agents, or human intervention
- Recent hands-on engineering experience in an AI-native company, product-led startup, or high-growth technology scale-up is strongly preferred
- Experience independently owning and delivering production software systems
- Strong problem-solving abilities and architectural judgment
- Entrepreneurial mindset with the ability to work independently in a fast-paced environment
- Excellent English communication skills
Nice to have
- Developing reusable agent orchestration frameworks or shared AI engineering libraries
- Building production multi-agent systems with specialized subagents
- Experience with PostgreSQL and distributed backend architectures
- Implementing advanced LLM observability and evaluation tools
- Optimizing LLM inference costs, response latency, and system performance
- Previous experience in an early-stage, AI-focused product engineering team
How to get hired
- 1Initial Screening – Initial review of your experience and suitability for the position
- 2Recruiter Interview (30 minutes) – Background, relevant experience, expectations, and availability
- 3Hiring Manager Interview (30 minutes) – Technical ownership, previous projects, and engineering approach
- 4System Design Interview (60 minutes) – Agentic architecture, scalability, orchestration, reliability, and evaluation
- 5Technical Interview (60 minutes) – Practical software engineering and applied AI capabilities
- 6Team Interview (45 minutes) – Collaboration, communication, and product mindset
- 7Optional Founder Interview (30 minutes) – Final discussion about company vision and alignment
Apply
About AIDA Recruitment
AIDA Recruitment is recruiting on behalf of a client: an AI-native technology company transforming the property management industry with an AI-powered platform that automates complex operational processes, integrates traditional businesses, and improves efficiency at scale.
Key facts
- approximately 20 people in engineering
- Client raised a $170 million Series B funding round
- Client has raised more than $260 million in total
- Client manages over 15,000 properties across the UK
- Engineering organization of approximately 20 people
- Small, autonomous teams of 2–3 engineers