Asurion
The Technology Analyst supports analysis, solution design, and delivery across technology initiatives. This role translates business needs into clear requirements, evaluates systems and data, and partners with engineering to implement improvements. The analyst coordinates testing, documentation, and change management to enable reliable, compliant solutions. Success requires structured problem solving, stakeholder collaboration, and disciplined execution to enhance service quality, performance, and operational efficiency. AI Delivery Engineer is responsible for independently supporting standard-complexity technology initiatives across business analysis, requirements engineering, AI-enabled SDLC delivery, quality validation, and requirement-to-test traceability. This role combines Technology Analyst and Quality Assurance Engineering responsibilities within a unified AI-enabled delivery model. The SDLC engineer works as part of the TA and QA function to gather requirements, structure business intent, generate and validate AI-assisted delivery artifacts, support test coverage, and ensure that requirements are clear, complete, testable, and traceable throughout delivery. At this level, the engineer independently produces and validates AI-enabled artifacts across both TA and QA domains, including AI-ready Business Requirement Documents, user story packages, acceptance criteria, business rules, workflow specifications, test scenarios, test case drafts, traceability matrices, quality review documentation, defect analysis summaries, and release readiness inputs for standard-complexity projects. The AI Delivery engineer uses AI tools to accelerate and improve requirements documentation, stakeholder analysis, workflow modeling, user story creation, acceptance criteria definition, test scenario generation, test case review, defect analysis, release readiness reporting, and SDLC artifact validation. Essential Job Skills/Duties Business Analysis and Requirement Engineering Elicit, analyze, and document business requirements for standard-complexity projects using structured analysis techniques and established prompt frameworks. Produce complete, AI-ready Business Requirement Documents (BRDs) for defined project scopes. Translate business requirements into structured prompts, context models, and user story packages. Document current-state and future-state process workflows using AI-assisted modeling tools. Define clear acceptance criteria, business rules, and workflow specifications for assigned work. Coordinate with business stakeholders to clarify requirements and manage scope changes independently. AI-Driven SDLC Orchestration Design and execute AI workflows for standard SDLC deliverables including user stories, test cases, and technical specifications. Independently validate AI-generated outputs for quality and alignment with business requirements. Support AI-assisted code generation and documentation activities, reviewing outputs before delivery. Manage backlog refinement activities with AI augmentation for assigned projects. AI Agent Development and Management Configure, maintain, and tune existing AI agents for routine use cases. Define prompt updates and interaction pattern adjustments to improve agent performance. Monitor agent performance metrics and identify issues requiring escalation. Contribute to prompt libraries and maintain knowledge artifacts for team use. AI Governance and Quality Assurance Apply established quality frameworks when reviewing and approving AI-generated deliverables. Ensure traceability between requirements and AI-generated artifacts for assigned projects. Identify gaps in existing governance checklists and propose improvements. Comply with all AI risk, compliance, and auditability requirements. Process Optimization and Collaboration Identify opportunities to improve established AI-enabled workflows and propose solutions. Contribute to SDLC automation playbooks and shared documentation. Support onboarding and guidance for Level 1 team members as needed. Participate in retrospective and process improvement discussions with actionable insights. CORE COMPETENCIES Expected Proficiency Business Solid business analysis and requirements documentation skills. Independently manages standard stakeholder interactions and moderately complex requirement scenarios within defined scope. Applies structured analysis and AI-assisted tools to produce complete, traceable BRDs and user story packages. Technical Working knowledge of SDLC, Agile delivery, and software testing; apply CI/CD and DevOps concepts to workflow design. AI & Automation Applied proficiency in prompt engineering and AI workflow execution. Configures and maintains existing AI agents within established frameworks. Understands LLM capabilities and limitations in delivery contexts. Developing skill in AI output validation, quality assessment, and governance compliance. Collaboration Proactive communicator; self-manages workload and priorities; participates in team improvement initiatives; provides guidance to junior team members. KEY DELIVERABLES AI-Ready Business Requirement Documents (BRDs) for standard-complexity projects Structured User Story Packages with acceptance criteria AI Agent configuration updates and prompt library contributions Validated AI-generated SDLC artifacts (test cases, specs, documentation) Quality review logs and traceability matrices Process improvement proposals and playbook contributions Required Education, Skills And Experience Education Degree: Bachelor’s degree in Information Systems, Computer Science, Engineering, Business Administration, or a related field; or equivalent practical experience. Required Experience Delivery experience: 1–3 years in technology analysis, business analysis, software quality assurance, software testing, or a related software delivery role. Agile delivery: Demonstrated experience working in Agile environments; familiarity with sprint ceremonies, backlog refinement, and cross-functional delivery team collaboration. AI exposure: Hands-on exposure to AI tools, prompt engineering concepts, or AI-assisted delivery workflows; genuine interest in developing applied AI orchestration proficiency. Stakeholder collaboration: Experience working across product, engineering, QA, and business stakeholder groups to clarify requirements and validate delivery outputs. Required Skills Requirements and analysis: Foundational knowledge of requirements documentation, user story writing, acceptance criteria definition, business rules documentation, and SDLC fundamentals. Business analysis: Working knowledge of structured analysis techniques including process modelling, stakeholder analysis, and scope definition within defined project parameters. AI-assisted delivery: Applied proficiency with AI tools for requirements generation, test case drafting, document automation, or equivalent TA and QA delivery use cases. Prompt engineering: Basic prompt engineering skills; ability to structure context models, apply established prompt templates, and refine AI-generated outputs for TA and QA tasks. Quality assurance: Familiarity with test case design, defect classification, test coverage principles, and AI output validation using established quality checklists. Communication: Strong written and verbal communication skills; ability to produce clear, structured, stakeholder-ready documentation, reports, and requirements artifacts. Self-management: Ability to manage assigned workload and priorities independently within a delivery team structure; proactive in surfacing blockers and escalating risks early. Preferred Licences / Certifications Certified ScrumMaster (CSM) or equivalent Agile credential. Business analysis certification — CBAP (Certified Business Analysis Professional) or CCBA. Data analytics certification or equivalent coursework. Microsoft AI Fundamentals (AI-900) or equivalent AI literacy credential. Prompt engineering certification or coursework (e.g., DeepLearning.AI, Microsoft Copilot Studio, or equivalent). Required Soft/Leadership Skills Clear, concise written and verbal communication. Structured problem solving and critical thinking. Stakeholder collaboration and expectation management. Time management and prioritization under deadlines. Adaptability in evolving business and technical contexts. Required Education & Experience Bachelor's degree in IT or related field. Three or more years in technology analysis. Experience supporting enterprise applications. Track record delivering process and system improvements. Preferred Education & Experience Master's degree in information systems or similar. Experience in Agile product delivery teams. Background in cloud platforms and data pipelines. Supervisory Responsibilities TRAVEL REQUIREMENTS (bulleted) Travels: Occasional for project or training needs. % of Time: Up to 10 percent. Overnight Travel: Rare, as business needs dictate. PHYSICAL DEMANDS & WORKING CONDITIONS (bulleted) Stationary Position: Frequently Vision: 20/20 corrected vision Hearing: Receive detailed information if spoken to
Asurion
