Business Systems Analyst

AI Business Systems Analysis

Location: REMOTE

Duration: 12-18+mths Contract

Must have:

• Strong Business Systems Analysis
• API, AI & Technical Contract Definition
• Context Engineering & AI-Assisted Development
• End-to-End Traceability, Testing & Validation
• Prototyping & Workflow Design
• Financial mortgage industry
• Strong communication
• LinkedIn Page

Role Summary: Converts business outcomes, architecture intent, and platform capabilities into structured specifications that can be consumed by engineers and AI coding agents. This role is central to the agentic delivery model: it produces the context, contracts, acceptance criteria, and validation logic required to turn ambiguity into executable work.

Key Responsibilities
Translate product goals, architecture decisions, stakeholder needs, and platform constraints into clear implementation-ready specifications.
Author platform capability definitions, API contracts, data contracts, event contracts, agent contracts, non-functional requirements, and testable acceptance criteria.
Create structured context packages for AI-assisted development, including business rules, workflow definitions, edge cases, sample payloads, user journeys, and validation expectations.
Maintain traceability from business objective to requirement, design artifact, test scenario, release criterion, and production outcome.
Partner with Product Owners, Architects, Engineers, and SMEs to refine backlogs, decompose work, clarify dependencies, and reduce cross-team coordination friction.
Define test scenarios and quality validation patterns so QA is embedded into the requirements-to-context pipeline rather than handled as a downstream handoff.
Maintain reusable specification templates, standards, glossaries, and golden-path documentation for teams.
Validate delivered functionality against intended outcomes and identify gaps between requirement, implementation, and operating behavior.
Strong business analysis, systems analysis, requirements engineering, and technical documentation skills.
Ability to work with API specifications, integration patterns, data schemas, workflow definitions, and service contracts.
Experience creating user stories, acceptance criteria, scenarios, test cases, process flows, and implementation artifacts.
Familiarity with agile delivery, product backlogs, QA automation concepts, and AI-assisted development workflows.
Ability to communicate effectively with business, engineering, architecture, security, and operations stakeholders.
Acts as a multiplier for engineers by creating high-quality context that lets AI agents produce better first-pass outputs.
Owns precision and clarity in a model where thin coordination surfaces replace recurring clarification meetings.