Intelligence Automation Business Analyst

Responsibilities

• Analyze stakeholder needs and convert them into detailed, context-rich Product Requirement Documents (PRDs) using Markdown formatting.
• Collaborate with engineers, architects, developers, UX specialists, and product managers to develop user stories and acceptance criteria aligned to mission requirements.
• Validate AI-generated code and outputs for correctness, quality, and alignment with product and architectural standards.
• Leverage AI-assisted tools to support PRD-to-code workflows, establishing constraints, rules, and patterns that guide AI development environments.
• Identify opportunities to automate workflows, streamline product development, and enhance user experience across digital capabilities.
• Track emerging technologies, incorporate multidisciplinary feedback, and contribute to rapid product iterations and feature refinement.

Qualifications

• 3+ years of experience as a Technical Business Analyst, Product Analyst, or Product Manager in an agile software development environment.
• 2+ years of experience with AI-assisted coding and product design tools such as GitHub Copilot, ChatGPT, Cursor, Claude, or Figma AI.
• Ability to translate stakeholder needs into structured PRDs including user stories and acceptance criteria using Given/When/Then formatting.
• Knowledge of prompt engineering concepts such as role, context, constraints, and output formatting.
• Knowledge of Agile delivery practices and standard Markdown or Git workflows.
• Ability to review code syntax, understand basic API integrations, and collaborate effectively with engineering teams.
• Ability to obtain and maintain a Public Trust or Suitability/Fitness determination.
• Bachelor’s degree (Preferred).
• Experience defining AI-specific performance metrics such as hallucination thresholds, latency targets, or model quality criteria.
• Experience driving AI-assisted PRD-to-code workflows, including setting rules, constraints, and scopes in AI development environments.
• Experience conducting structured reviews of AI-generated code outputs.
• Ability to synthesize multidisciplinary feedback from UX, legal, or engineering teams into rapid product iterations.