Summary
✨ AI‑Generated
An AI engineer is sought to design, build, and deploy intelligent agents and generative AI solutions for real-world business use cases. The role combines LLM orchestration, agent frameworks, backend engineering, automation, and production deployment to create reliable AI-powered systems.
Highlights
Build and deploy production-grade AI agents and generative AI systems, moving beyond prompt engineering into end-to-end solution architecture, backend development, orchestration, and deployment.
Description
Job Title: Artificial Intelligence Engineer
Location: Malta – Hybrid Working
About Cluster365:
Cluster365 is an AI technology company behind an Agentic Orchestration Platform designed to help businesses connect and coordinate multiple AI models, tools, data and workflows in one place.
The platform combines multi-LLM capabilities, intelligent agents, automation, scheduling and event-driven workflows to help teams streamline complex processes and build reliable, scalable AI-powered solutions.
Role Overview:
This role is responsible for designing, building, and deploying intelligent AI agents and generative AI systems that solve real business problems.
You will move beyond prompt optimization into full AI solution architecture — combining LLM orchestration, agent frameworks, backend development, and production deployment.
Duties and Responsibilities:
Design & Build AI Agents
Architect and implement autonomous and semi-autonomous AI agents capable of reasoning, planning, tool usage, and multi-step task execution.Design agent workflows using frameworks such as LangChain, LangGraph, or similar orchestration tools.Implement memory systems, retrieval pipelines, and tool integrations.
Develop Production-Ready AI Systems
Build robust Python-based backend services that integrate with LLM APIs and internal systems.Develop scalable architectures for AI features (REST APIs, microservices, serverless functions).Ensure reliability, performance, observability, and cost optimization of AI services.
Orchestrate LLM Workflows
Design complex prompt chains and structured output pipelines.Implement RAG (Retrieval-Augmented Generation) systems using vector databases.Create evaluation frameworks to measure model performance, hallucination rate, and business impact.
Integrate & Collaborate
Work closely with Product teams to translate business problems into AI-driven solutions.Collaborate with Engineering to deploy AI services into production environments.Align AI solutions with compliance, safety, and governance standards.
Drive AI Innovation
Stay at the forefront of LLM advancements, agentic architectures, and emerging AI tooling.Prototype and test new approaches to improve automation, reasoning accuracy, and system intelligence.Continuously improve system performance through experimentation and evaluation.
Person Specifications:
Hard Skills - Must-have:
AI Agent Development — Hands-on experience building AI agents with tool usage, memory, and multi-step reasoning.Advanced Python Proficiency — Strong backend development skills including API design, async processing, data pipelines, and integration patterns.LLM Integration — Deep experience integrating OpenAI or similar APIs into production systems.RAG & Vector Databases — Experience implementing semantic search and retrieval pipelines using Pinecone, Weaviate, FAISS, or similar tools.Evaluation & Testing — Experience designing evaluation loops for LLM outputs, including prompt testing, benchmarking, and guardrail implementation.
Hard Skills - Nice-to-have
AI Orchestration Frameworks — LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar.Cloud & Deployment — Experience with Docker, Kubernetes, AWS, GCP, or serverless environments.Data Engineering Basics — Handling embeddings, ETL pipelines, and structured/unstructured data transformation.Monitoring & Observability — Experience with logging, tracing, and AI system performance monitoring.
Soft Skills - Must‑have:
Systems Thinking — Ability to design end-to-end AI solutions, not just isolated prompts.Problem Decomposition — Strong capability to break down complex business problems into agent-based workflows.Technical Communication — Comfort explaining AI architecture decisions to both technical and non-technical stakeholders.Ownership Mentality — Takes responsibility for delivering production-grade, reliable AI systems.
Soft Skills - Nice‑to‑have:
Strategic Vision — Understands how AI automation drives measurable business value.Leadership & Mentorship — Ability to guide teams on best practices in AI engineering and agent design.
KPIs
AI Agent Task Success RateSystem Reliability & LatencyReduction in Manual Work Through AutomationTime-to-Prototype for New AI SolutionsModel Accuracy & Hallucination ReductionProduction Deployment Velocity
Commitment to Diversity: Cluster 365 is dedicated to equal opportunity for all staff.
Applications from individuals are encouraged regardless of age, disability, sex, gender reassignment, sexual orientation, pregnancy and maternity, race, religion or belief, and marriage or civil partnerships.
Personal data is processed in accordance with EU GDPR.
CVs are retained for 12 months, and we may contact you regarding other suitable roles during this period.
Cluster 365 is committed to equality of opportunity for all staff and applications from individuals are encouraged regardless of age, disability, sex, gender reassignment, sexual orientation, pregnancy and maternity, race, religion or belief and marriage and civil partnerships.
Personal data are processed in accordance with EU and UK GDPR and our Privacy Policy.
CVs are retained for 12 months, and we may contact you regarding other suitable roles during this period’