AI Engineer Remote

Location: Brighton (Hybrid) / Europe (Remote)About AttercopAttercop is a knowledge engineering and agentic AI company built specifically for private equity and professional services. We turn fragmented hard to use information into structured intelligence and deploy autonomous AI agents that make decisions not just recommendations. Our systems deliver faster insights operational efficiency gains and real value creation across the PE lifecycle from diligence and data organisation to portfolio wide OverviewYoull design build and integrate advanced AI models into real software systems. This role sits at the intersection of software engineering data science and MLOps turning research into robust scalable production-ready AI ResponsibilitiesModel EngineeringBuild functional AI services from architectural designsOrchestrate data ingestion inference flows and output pipelinesOptimise latency memory and throughputImplement testing validation and error/bias analysisAgentic WorkflowsDesign multi-agent systems using LangChain LangGraph or Microsoft Agent FrameworkImplement reasoning loops (e.g. ReAct)Integrate tools APIs databases and memory systemsDevelop safety and reliability checks for agent behaviourData EngineeringBuild scalable ETL/ELT pipelinesPerform feature engineering and advanced data prepIntegrate SQL/NoSQL data lakes warehouses and streaming APIsEnsure compliance with GDPR/CCPA and internal governanceMLOps & DeploymentDeploy AI services on Azure using REST APIsUse Docker Kubernetes for scalable production workloadsBuild ML-focused CI/CD pipelinesImplement monitoring drift detection logging alerting and retrainingManage infrastructure with TerraformCandidate RequirementsExperience2 years as an AI Engineer or Software Engineer with strong AI/ML exposureTechnical SkillsAdvanced Python (asyncio type hinting Pydantic)Backend/API development with FastAPI/Flask/DjangoAgentic frameworks (LangChain LangGraph Microsoft Agent Framework)LLM orchestration RAG prompt engineeringCloud (Azure preferred) Docker KubernetesIaC (Terraform)PostgreSQL plus exposure to NoSQL and vector databasesCI/CD monitoring observability ML-specific drift detectionCollaboration & CommunicationWork effectively with data scientists PMs and stakeholdersCommunicate technical decisions clearlyMaintain strong documentation across pipelines and architectures