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Asurion is a global tech solutions company delivering AI-enabled software delivery at scale. The Level 3 AI Delivery Engineer leads complex AI delivery programs spanning multiple workstreams, owning requirements engineering, SDLC orchestration, and quality governance.
You will design agent configurations, governance standards, and risk mitigation strategies while mentoring Level 1–2 engineers. This senior role requires 4–7 years in technology analysis, AI delivery, and software quality
The Level 3 AI Delivery Engineer is a senior practitioner responsible for independently leading technology initiatives of moderate-to-high complexity across business analysis, requirements engineering, AI-enabled SDLC delivery, quality governance, and end-to-end traceability. Operating with full autonomy, the Level 3 engineer owns complete delivery programmes without day-to-day supervision and serves as the primary escalation point for Level 1 and Level 2 engineers facing complex technical, quality, and delivery challenges. This role combines Technology Analyst and Quality Assurance Engineering responsibilities within a unified AI-enabled delivery model at an advanced level. Where the Level 2 engineer applies established frameworks, the Level 3 engineer creates, refines, and governs them. This includes architecting AI-enabled delivery workflows, designing and governing agent configurations, defining quality standards adopted by the broader team, and driving systematic improvement in TA and QA delivery practices across the function. At this level, the engineer independently owns complex, multi-stakeholder AI delivery programmes and produces the full range of TA and QA artifacts at expert quality — including comprehensive BRDs for complex system changes, multi-stream user story packages, advanced acceptance criteria sets, cross-domain traceability frameworks, test strategies for complex programmes, and quality governance documentation for team-wide adoption. The Level 3 engineer drives AI-first delivery practices, accelerates team capability, and contributes meaningfully to the organisation's AI delivery maturity
Requirements engineering for complex, multi-team projects and programmes, independently managing ambiguous scope, competing priorities, and cross-functional stakeholder dependencies. Design and govern AI-enabled requirements workflows — including context model architecture, prompt framework design, and BRD generation standards — adopted by the broader team. Own senior stakeholder relationships across product, engineering, QA, and business domains; independently facilitate complex requirements workshops, decision sessions, and escalation meetings. Translate complex, multi-domain business intent into comprehensive AI-consumable models including advanced process flows, integration specifications, risk registers, and dependency maps. Define and enforce acceptance criteria quality standards, business rules completeness thresholds, and requirements traceability standards for team-wide adoption. Resolve ambiguous, conflicting, or incomplete requirements through independent analysis and targeted stakeholder engagement without escalation to senior leadership.
Own end-to-end AI delivery workflows for complex programmes spanning multiple workstreams, delivery phases, and cross-functional teams. Define agent sequencing, handoff protocols, human review gates, and validation checkpoints for multi-phase AI-enabled SDLC delivery at programme scale. Independently resolve AI workflow failures, quality exceptions, and cross-team delivery conflicts that Level 1 and Level 2 practitioners escalate; implement lasting remediation. Lead AI-assisted programme planning including backlog architecture, sprint sequencing, dependency resolution, and release planning for complex, multi-team initiatives.
Design, build, and maintain specialised AI agents for requirements analysis, workflow modelling, test design, automation generation, and quality validation use cases. Define agent interaction patterns, permission boundaries, escalation protocols, and output quality standards that the team adopts as governance baselines. Lead agent improvement cycles including prompt engineering, model evaluation, output benchmarking, and performance optimisation across the team's AI delivery agent ecosystem. Establish and govern agent registry management, version control practices, and performance baseline documentation for the team's AI delivery infrastructure.
Design and own quality evaluation frameworks and acceptance thresholds for AI-generated artifacts across both TA and QA domains, adopted team-wide. Lead complex quality reviews for high-risk, high-priority deliverables; define and enforce team-level quality standards, governance protocols, and sign-off procedures. Identify systemic AI output errors, conduct root-cause analysis, and implement prompt engineering improvements and workflow corrections that benefit the whole team. Own AI risk, compliance, and auditability standards for the team; represent the delivery function in governance forums, audit processes, and compliance reviews.
Process improvement initiatives across the TA and QA function; own delivery playbooks, SDLC automation standards, and quality governance frameworks for the team. Drive adoption of AI-first delivery practices across product, engineering, and QA teams; champion continuous improvement as a discipline, not a periodic activity. Mentor and develop Level 1 and Level 2 engineers; act as the primary technical escalation point for complex delivery, quality, and AI challenges across the team. Contribute to the team's AI delivery strategy, tooling evaluation, capability roadmap, and organisational AI maturity initiatives.
Domain Expected Proficiency at Level 3
Degree: Bachelor's degree in Information Systems, Computer Science, Engineering, Business Administration, or a related field; master's degree preferred.
Delivery experience: 4–7 years in technology analysis, business analysis, software quality assurance, AI-enabled software delivery, or related software delivery roles.
Complex programme delivery: Demonstrated experience independently leading delivery across complex, multi-team, or multiple-workstream initiatives without day-to-day supervision.
AI delivery leadership: Proven experience designing AI-enabled delivery workflows, building or governing AI agents, and driving measurable improvements in team AI delivery maturity.
Stakeholder ownership: Demonstrated experience owning senior stakeholder relationships across product, engineering, QA, and business domains; independently facilitated complex requirement sessions.
Asurion is a global tech solutions industry leader that creates a work culture where employees are valued, regardless of their level or position. Our products and services help nearly 300 million customers worldwide. The Asurion Way informs our values as colleagues and emphasizes that how we work matters just as much as the work itself. Here’s how we practice the Asurion Way: Customer First We provide our customers with excellent service through empathetic, helpful, and simple interactions. Our first step? To listen. One Team We believe that our success depends on collaborating, staying humble, and embracing diverse viewpoints. Divine Discontent We’re not afraid to roll up our sleeves and do more. We start small, scale with success, and tap into our full potential to deliver the best products and services. Act with Integrity We take ownership and pride in the work we do. We build trust-based relationships and do what’s right—even when no one is looking.
Asurion is an equal opportunity employer. We hire the best available person for the job regardless of marital status, sex, gender orientation, age, religious belief, race, nationality and ethnic origin, color, or disability.