Applied AI Engineer – LLM & Agentic Systems
AIDA projektai, MB
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Benefits offered by this job
Job summary
AIDA Recruitment is seeking an experienced Applied AI Engineer for an AI-native tech company in the UK. You will design and deploy production-grade AI agents, focusing on backend systems with TypeScript/Node.js and Python.
This remote role offers autonomy, equity, and growth in a fast-paced, engineering-driven environment. You will work on agent orchestration, tool integration, and scalable architectures while collaborating with product and data teams.
Qualifications
- 3+ years of professional software engineering experience with backend focus.
- Proven experience building and deploying LLM-powered agents in production.
- Experience with agent orchestration, tool calling, and context management.
- Strong architectural, testing, and CI/CD skills.
- Bachelor's degree in Computer Science or related field.
Responsibilities
- Design, build, and maintain production-grade LLM-powered agents and multi-agent systems.
- Develop agent workflows with decomposition, tool calls, outputs, orchestration, and feedback loops.
- Create scalable architectures connecting AI agents to backend services and databases.
- Collaborate with product managers and engineers to identify automation opportunities.
- Own features from architecture through deployment and monitoring.
- Improve observability, debugging, and fault tolerance.
Skills
Education
Tools
Job description
AIDA Recruitment is looking for an experienced Applied AI Engineer to join our client's rapidly growing, AI-native technology company in the UK.
Our client is transforming the property management industry by developing an AI-powered platform that automates complex operational processes, integrates traditional businesses, and improves efficiency at scale.
Following a $170 million Series B funding round, the company has raised more than $260 million and now manages over 15,000 properties across the UK.
You will join a growing engineering organization of approximately 20 people, working in small, autonomous teams of 2–3 engineers.
This is an opportunity to become an early core contributor to the company's agentic AI infrastructure, influence architectural decisions, and develop systems already supporting real business operations.
This is not an AI research or traditional Machine Learning position. We are looking for a strong backend software engineer who has built, deployed, and maintained AI agents in production.
Location: Fully Remote – UK & Europe (UK working hours)
Salary: €100,000–€150,000 annually
Contract: Full-time | Permanent or B2B
Equity: Competitive equity options
Tech Stack: TypeScript, Node.js, PostgreSQL, Python, LLMs, Agentic AI
Visa sponsorship: Sponsorship or visa transfers may be possible for candidates already based in London. New international relocation is not offered as standard.
- 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.
- 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.
- 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.
We are particularly interested in engineers who can demonstrate ownership of real production AI systems.
A strong candidate should be able to describe:
- A production AI agent: What did you build, what business problem did it solve, and how many users or transactions did it support?
- System architecture: How did you implement agent orchestration, tool integration, context management, and backend services?
- Evaluation: How did you measure agent quality? What evaluation dataset sizes, pass thresholds, or automated release checks did you use?
- Production challenges: What specific failure, hallucination, reliability issue, or latency problem did you encounter, and how did you resolve it?
- AI development practices: How do you use coding agents such as Claude Code or Codex in your daily engineering workflow?
- Your AI experience is limited to calling LLM APIs, prompt engineering, or building simple chatbot wrappers.
- You have built AI prototypes or proof‑of‑concepts but have not deployed and maintained agents in production.
- Your background is primarily in traditional machine learning, data science, computer vision, or academic AI research.
- Your experience focuses on MLOps or AI infrastructure without hands‑on ownership of agentic applications.
- You are primarily a frontend developer without substantial backend engineering experience.
- You have worked mainly on short‑term AI consulting projects without responsibility for a production product.
The key requirement is hands‑on engineering ownership of reliable, production‑grade agentic AI systems.
- Languages: TypeScript, JavaScript, Python
- Backend: Node.js, REST APIs, PostgreSQL
- AI: Large Language Models, Agentic Workflows, Multi‑Agent Systems
- AI Engineering: Tool Calling, Structured Outputs, Context Management, Orchestration
- Quality & Infrastructure: Agent Evaluations, Observability, CI/CD, Automated Testing
- Development Tools: Claude Code, Codex, or similar AI coding agents
- Real production AI: Work on agentic systems already supporting business operations rather than experimental AI projects.
- Strong financial backing: Join a fast‑growing technology company with over $260 million in funding.
- Architectural ownership: Help establish the core infrastructure, engineering patterns, and technical standards for AI systems.
- Small, autonomous teams: Work directly with experienced engineers, product specialists, and engineering leadership.
- Professional growth: Opportunity to influence product direction, propose new initiatives, and take ownership of technically challenging projects.
- Remote flexibility: Work remotely from eligible UK or European locations.
- Competitive compensation: €100,000–€150,000 annually, with equity opportunities.
- AIDA Recruitment Initial Screening – Initial review of your experience and suitability for the position.
- Recruiter Interview (30 minutes) – Background, relevant experience, expectations, and availability.
- Hiring Manager Interview (30 minutes) – Technical ownership, previous projects, and engineering approach.
- System Design Interview (60 minutes) – Agentic architecture, scalability, orchestration, reliability, and evaluation.
- Technical Interview (60 minutes) – Practical software engineering and applied AI capabilities.
- Team Interview (45 minutes) – Collaboration, communication, and product mindset.
- Optional Founder Interview (30 minutes) – Final discussion about company vision and alignment.
The interview process typically takes approximately two weeks, depending on candidate availability.
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