Senior Business Analyst

About the role

You will translate business intent into system-level precision: domain models, state machines, integration contracts, and executable policy rules that AI agents and engineering teams can act on without interpretation gaps. You will own the full specification lifecycle - from stakeholder discovery through system design validation to behavioural sign-off - and you will set the standard others follow. This is a role for someone who has experience in both the insurance business and technical dimensions of requirements in complex environments, and who is ready to apply that dual expertise at the frontier of AI-augmented enterprise delivery.

Responsibilities

• Strategic Discovery and Business Requirements Leadership
• Own end-to-end requirements across multiple concurrent programmes - translating business strategy into delivery-ready artefacts without loss of intent or regulatory nuance
• Lead structured discovery with C-suite sponsors, business owners, underwriters, claims leaders, and Product leadership across insurance lines (commercial, specialty, claims, reinsurance, financial reconciliation)
• Employ GenAI tools to produce requirements that are precise enough for agent execution: not narrative documents, but structured artefacts with unambiguous scope, measurable acceptance criteria, and explicit constraint boundaries
• Hold scope discipline under executive pressure; own sign-off without escalation and defend decisions with documented rationale
• Conduct gap analysis between legacy system behaviour and target state design - identifying data quality issues, integration constraints, and migration risks at specification level before build begins
• Perform SQL-based data interrogation independently to validate assumptions, profile source data, and verify transformation logic prior to engineering handoff
• Assess system-level feasibility of proposed solutions: identify architectural constraints, integration boundaries, and non-functional implications early in the discovery cycle
• Author integration system behaviour under partial failure, downstream unavailability, and data inconsistency scenarios - as first-class specification artefacts
• Collaborate with the Tech Lead and Enterprise Architecture to ensure NFRs are architecturally validated before sprint commitment
• AI Agent Contract Authoring and Governance
• Produce and own the structured artefacts that govern AI agent execution: canonical input/output examples, error catalogues, prohibited behaviour constraints, system boundary definitions, and integration failure contracts
• Define prompting strategies, model constraint boundaries, hallucination guardrails, and human-in-the-loop control points for GenAI-enabled features - grounded in system-level understanding of what the underlying data and integrations can reliably support
• Establish programme level AI specification best practices
• Lead the BA/SA-agent execution loop across complex, multi-dependency initiatives: classify outcomes, author targeted re-submission instructions, and drive convergence to verified output
• Provide final behavioural sign-off once outputs meet acceptance criteria across all specification artefacts - business, system, regulatory, and integration dimensions
• Partner with engineering principals, data architects, and GenAI SMEs throughout the SDLC to ensure requirements fidelity is maintained end-to-end
• Insurance Domain and Regulatory Authority
• Bring deep insurance domain expertise to specification decisions - ensuring regulatory intent is embedded as executable policy rules and system constraints, not compliance footnotes
• Serve as the domain authority bridging underwriting, claims, actuarial, finance, and operations stakeholder communities with engineering and AI delivery teams
• Identify where legacy system constraints, poor data quality, or integration boundaries create delivery risk - and define mitigation strategies at specification level before they become build defects
• Set and maintain specification quality standards across the BA and SA communities; review and technically sign off the work of junior practitioners
• Lead or contribute to the BA-to-SA upskilling programme; build internal capability in systems modelling, integration design, and AI-ready specification practice

Requirements

• Essential
• 10-15 years of progressive experience spanning Business Analysis and Systems Analysis, with a substantial portion in insurance or regulated financial services
• Deep insurance domain expertise across at least two of: commercial lines policy administration, claims, specialty, reinsurance, financial reconciliation, or regulatory reporting
• Proven ability to produce requirements that hold under engineering scrutiny, regulatory review, and AI agent execution - with minimal rework
• Expert-level systems modelling: domain models, state machines, data flow diagrams, sequence diagrams, ERDs, and field-level data specifications
• SQ

Additional Information

Senior Business & Systems Analyst - AI-Native Delivery

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