Remote AI Business Process Engineer (Platform Specs Analyst)
Duration: 12-18+ months/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 is a plus not required
- Strong communication
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.
Preferred Experience / Capabilities
• 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.
Differentiators
• 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.
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