AI Delivery Engineer 3

Asurion; Hinoba-an; On-site; PHP 1,800,000 - 3,000,000; Full time

Job summary

Asurion is seeking a Level 3 AI Delivery Engineer to independently lead complex AI-enabled delivery programmes spanning multiple workstreams. You will own end-to-end delivery, architect AI workflows, govern agent configurations, and set quality standards adopted by the team.

This role combines technology analysis, QA, and process improvement at an advanced level, with responsibility for cross-domain artefacts and stakeholder management.

Qualifications

• Advanced requirements engineering for complex, multi-stakeholder projects.
• Proven leadership of delivery across AI-enabled software projects.
• Experience designing AI-enabled delivery workflows and governance frameworks.

Responsibilities

• Lead requirements workshops and manage senior stakeholder relationships across product, engineering, QA, and business domains.
• Own end-to-end AI delivery workflows, including agent sequencing and human review gates.
• Design, build, and govern AI agents and related quality validation processes.
• Develop and maintain AI delivery governance standards and cross-domain traceability frameworks.
• Mentor Level 1 and 2 engineers and drive capability improvements across the team.

Skills

Advanced requirements engineering

Business analysis leadership

AI workflow architecture

Prompt engineering (advanced)

Quality governance

Senior communications

Technical leadership

Education

Bachelor's degree in Information Systems/Computer Science/Engineering/Business

Master's degree preferred

Job description

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

Business Analysis and Requirement Engineering Lead

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.

AI-Driven SDLC Orchestration Architect

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.

AI Agent Development and Management

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.

AI Governance and Quality Assurance

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 Optimisation and Collaboration Lead

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.

Core Competencies

Domain Expected Proficiency at Level 3

• Business Expert – business analysis and AI context engineering. Independently leads complex multi-stakeholder requirements programmes; owns senior stakeholder relationships across product, engineering, QA, and business domains.
• Technical Expert – SDLC, Agile programme management, and software quality strategy. Architects AI delivery workflows for complex, multi-team programmes; resolves advanced technical and delivery issues independently.
• Collaboration – leads by influence; mentors and develops Level 1 and Level 2 engineers; drives team-level improvement initiatives and delivery standards.

Key Deliverables

• AI-Ready BRDs for complex, multi-team projects and programmes.
• Advanced User Story and Epic Packages with multi-domain acceptance criteria.
• AI Agent Design Specifications and Configuration Standards for team adoption.
• Quality Evaluation Frameworks and Governance Standards for TA and QA domains.
• Cross-domain Traceability Frameworks and Programme Traceability Maps.
• Delivery Playbooks, SDLC Automation Standards, and Process Improvement Roadmaps.
• Mentoring Plans and Technical Development Support for Level 1 and Level 2 Engineers.

Required Education, Skills and Experience

Education

Degree: Bachelor's degree in Information Systems, Computer Science, Engineering, Business Administration, or a related field; master's degree preferred.

Required Experience

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.

Required Skills

• Advanced requirements engineering: Expert-level BRD authoring, multi-domain process modelling, advanced acceptance criteria design, and cross-system traceability for complex, multi-team programmes.
• Business analysis leadership: Independently leads complex stakeholder sessions; resolves conflicting requirements and competing priorities without escalation; defines team requirements standards.
• AI workflow architecture: Designs and governs multi-step AI delivery workflows; defines agent sequencing, validation protocols, exception handling, and human review gate criteria.
• Prompt engineering (advanced): Designs prompt frameworks, context model architectures, and knowledge library structures for team-wide adoption and continuous improvement.
• Quality governance: Designs quality evaluation frameworks; defines and owns quality standards and acceptance thresholds for both TA and QA artifact types adopted by the team.
• Communication (senior): Produces executive-ready documentation, programme-level status reports, and governance artifacts for senior stakeholder and leadership consumption.
• Technical leadership: Acts as primary escalation point for complex delivery and AI challenges; mentors junior practitioners; identifies and drives team capability development opportunities.

Asurion

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.