QualityKiosk Technologies
Website:
qualitykiosk.com
Company:
https://www.linkedin.com/company/qualitykiosk-technologies
Seniority: Director
Industries: IT Services and IT Consulting
Job details:
JD # Delivery Director – AI Reliability Programs
Role Overview
We are looking for an experienced Program Manager to lead strategic Software Quality Engineering and AI Reliability programs for enterprise customers. This role requires strong expertise in software delivery, AI-enabled engineering ecosystems, quality transformation and large-scale program governance.
The ideal candidate will have a strong engineering foundation, deep understanding of SDLC and quality engineering practices and demonstrated experience managing complex customer programs focused on software reliability, AI reliability, and business outcomes.
The role involves leading cross-functional teams comprising Test Managers, Test Architects, Quality Engineers, and AI Engineers while driving operational excellence, customer confidence and program growth.
Key Responsibilities
- Lead large-scale Software Quality Engineering and AI Reliability programs across enterprise customers
- Drive end-to-end governance across SDLC stages including requirements, development, testing, release, production validation, and operational reliability
- Oversee delivery teams consisting of Test Managers, Test Architects, Quality Engineers, and AI Engineers
- Ensure software and AI systems meet reliability, performance, quality, observability, and governance standards
- Lead AI-led quality transformation initiatives including intelligent test automation, AI-assisted testing, evaluation frameworks, and AI observability
- Partner with customers to define quality strategies, reliability roadmaps, governance models, and measurable business outcomes
- Own program delivery, financial performance, profitability, and overall P&L management
- Build strong client relationships that drive customer retention, confidence, and business growth
- Manage risks, escalations, dependencies, and stakeholder communication across multiple programs and teams
- Operate effectively in fast-changing environments with evolving technologies, delivery priorities, and customer expectations
- Mentor delivery leaders and create a culture focused on accountability, engineering excellence, and continuous improvement
Required Experience & Qualifications
- 15+ years of experience in software engineering, quality engineering, and program management
- Proven track record of leading enterprise-scale software development, quality engineering, or AI reliability programs
- Strong understanding of SDLC, Quality Engineering, DevOps, CI/CD, test automation, release governance, and production assurance
- Prior hands-on experience as a software developer/engineer early in career
- Demonstrated expertise in AI/GenAI programs, AI evaluation methodologies, AI observability, and reliability engineering
- Experience leading multi-disciplinary teams including Test Managers, Architects, and AI Engineering teams
- Proven success in client retention, customer relationship management, and business growth initiatives
- Experience owning program financials and P&L responsibilities
- Excellent executive communication, stakeholder management, and problem-solving skills
- Strong adaptability and ability to lead in environments with continuous change and ambiguity
What We Will Evaluate
Candidates will be evaluated based on:
- The measurable impact they created in customer programs
- Their ability to improve software and AI reliability outcomes at scale
- Examples of transformation, optimization, or modernization initiatives they led
- Their approach to handling complex delivery and stakeholder challenges
- Learnings derived from failures, escalations, and program pivots
- Depth of ownership, leadership maturity, and execution capability
- Practical understanding of AI-led software quality and reliability engineering
Ideal Candidate Profile
- Engineering-led program leader with strong business acumen
- Deeply customer-focused and outcome-oriented
- Strong understanding of both traditional software systems and AI-driven engineering ecosystems
- Comfortable operating across executive discussions and technical delivery governance
- High ownership mindset with strong execution discipline
- Able to balance quality rigor, innovation, speed, and operational reliability in enterprise environments
Click on Apply to know more.
