Jobs in London - LLM, RAG & Agentic AI Engineer – Insurance Sector • Central London

Company: Staffworx

Central London

LLM, RAG & Agentic AI Engineer – Insurance SectorOccasional travel client offices and two trips to London HQ per monthRole Overview Lead the design and delivery of AI-native transformation initiatives for insurance clients, spanning agentic systems, retrieval architectures, semantic layers and decision intelligence. This is a senior, hands-on consulting role combining deep AI engineering expertise with strong client-facing presence, shaping both insurance-specific client outcomes and the firm’s long-term AI engineering capability.As demand accelerates across claims automation, underwriting decision support, policy servicing, fraud detection, compliance and operational efficiency, the consulting practice is expanding its engineering capability across agentic systems, retrieval, ontologies and AI-enabled execution within regulated insurance environments.The Consulting Engineer is a hands-on AI systems builder who combines engineering depth with commercial and product thinking to design, build and deploy LLM- and agent-driven solutions for insurers, brokers and value chain partners.You will work directly with senior insurance stakeholders (Claims, Underwriting, Operations, IT, Risk, Compliance, Actuarial) and alongside consulting and orchestration roles, translating complex insurance problems into safe, reliable and auditable AI solutions.Key AccountabilitiesClient-Facing AI Engineering & Agentic System Design (Insurance-Focused)You will design and deliver production-grade AI systems for insurance clients, including:LLM-powered applications for claims handling, underwriting support, policy servicing, document processing and customer operationsMulti-agent architectures for insurance workflows, including triage, decision support, escalation, delegation and human-in-the-loop controlsRetrieval and vector-based systems over policy wordings, endorsements, claims files, loss runs, underwriting guidelines and regulatory documentationSemantic layers, ontologies and knowledge models aligned to insurance data structures, coverage logic and risk taxonomiesIntegrations with core insurance platforms (claims systems, PAS, underwriting workbenches), data warehouses and third-party providersPrompt engineering at scale with regulatory guardrails, explainability, traceability and auditabilitySafety constraints for hallucination control, coverage interpretation accuracy and customer-facing use casesTechnical Discovery, Feasibility & Solution ArchitectureWorking closely with consulting counterparts, you will:Translate ambiguous insurance challenges into clear, feasible AI solutionsAssess client data maturity, policy document quality, legacy platforms and security constraintsShape use cases across claims leakage reduction, underwriting efficiency, fraud detection and compliance automationWork directly with insurance SMEs to surface edge cases, exceptions, regulatory nuances and operational realitiesProduce clear, concise technical artefacts suitable for regulated, risk-aware client audiencesDelivery Excellence, AI Ops & Reliability (Regulated Environments)You will ensure solutions are enterprise-ready and regulator-safe by:Implementing evaluation frameworks for accuracy, coverage interpretation, decision consistency and biasDesigning monitoring, logging and tracing suitable for regulated insurance environmentsApplying governance, risk and compliance principles (eg audit trails, explainability, access controls)Supporting controlled releases and operational handover into insurer IT and operations teamsEnsuring reliability, reproducibility, performance and cost discipline at insurance scaleReusable Assets & Insurance AI Capability BuildingAs part of a consulting-led engineering practice, you will:Build reusable insurance-specific accelerators, agent patterns and reference architecturesContribute to internal playbooks covering claims, underwriting, policy servicing and compliance use casesShare emerging research, frameworks and AI trends relevant to the insurance sectorInfluence delivery methodology, technical standards and agentic design patterns for regulated industriesExperience & SkillsThis is a hands-on consulting engineering role. Candidates should bring:Experience in software engineering, AI engineering or applied data engineeringStrong hands-on experience with LLMs, embeddings, RAG pipelines and vector databasesExperience designing or implementing multi-agent systems or tool-calling frameworksStrong Python skills with experience building production-grade, regulated systemsExperience with at least one major cloud AI ecosystem (Azure/OpenAI, GCP/Vertex, AWS, Anthropic)Familiarity with semantic modelling, ontologies or knowledge graph concepts, ideally applied to complex domainsProven ability to rapidly prototype and validate solutions with business stakeholdersExperience working directly with clients in consulting, professional services or regulated enterprise environmentsInsurance domain experience (claims, underwriting, policy, risk, compliance or adjacent systems) strongly preferred