AI Strategic Consultant

Infosys; Bengaluru; On-site; INR 3,000,000 - 4,500,000; Full time

Job summary

Infosys is seeking a leader in Quality Engineering to oversee enterprise transformation initiatives. The ideal candidate will have over 15 years of extensive experience in quality engineering and a strong capability to lead large organizations through change. Responsibilities include designing governance models, advising on AI-driven quality engineering, and spearheading C-suite engagements. If you possess a Bachelor of Engineering and are passionate about innovation in quality practices, we invite you to apply.

Qualifications

• 15+ years of QE experience with enterprise-scale transformation exposure.
• Demonstrated ability to lead and advise large, complex organisations.
• Strong understanding of DevOps, CI/CD, cloud-native.

Responsibilities

• Lead end-to-end enterprise QE transformation and define target-state blueprints.
• Design governance and operating models for predictive quality practices.
• Support growth through C-suite advisory and presales leadership.

Skills

QE experience

AI-driven quality engineering advisory

Governance frameworks

Cost-of-quality analysis

Modern engineering fluency

Education

Bachelor of Engineering

Job description

Educational Requirements

Bachelor of Engineering

Service Line

Infosys Quality Engineering

Responsibilities

Lead endtoend enterprise QE transformation by assessing current capabilities, benchmarking maturity, and defining AIfirst target-state blueprints across people, process, and technology.

• Design intelligent governance and operating models that embed predictive, autonomous quality practices aligned to business outcomes, while driving rapid value through early wins.
• Enable sustainable change through executive alignment, change management, transition and knowledge transfer strategies, and reduced dependency on consulting support.
• Additionally, support growth through Csuite advisory, presales leadership, creation of proprietary IP, and market shaping via thought leadership and industry engagement.

Additional Responsibilities

GoodtoHave SkillsThese enhance differentiation and futureproof the role but are not strictly required for core execution: AIdriven quality engineering advisory Guiding adoption of intelligent testing, predictive risk analytics, and autonomous quality capabilities.

• AI risk assurance and trust frameworks Understanding AI model quality, bias detection, and data quality as QE expands into AIenabled products.
• Advanced quality intelligence and analytics mindset Leveraging observability, telemetry, and production insights to influence testing and governance strategies.
• Innovation and value realization focus Ability to distinguish genuine AIdriven lift from vendor hype and steer clients toward pragmatic value outcomes.

Technical and Professional Requirements

Mandatory Skills: These are essential for baseline success in an enterprise QE advisory leadership role: 15+ years of QE experience with enterprise-scale transformation exposure, Demonstrated ability to lead and advise large, complex organisations.

• QE strategy and operating model design: Defining multiyear QE roadmaps, governance frameworks, and risk-based quality strategies.
• Quality economics expertise: Cost-of-quality analysis, ROI articulation, and tying QE outcomes to business metrics (cost, speed, resilience).
• Risk-based and outcome-driven QE leadership: Driving measurable improvements in defect leakage, release velocity, reliability, and compliance.
• Modern engineering fluency (at advisory level): Strong understanding of DevOps, CI/CD, cloud-native, and platform engineering concepts to translate technical complexity into actionable quality guidance (without hands-on pipeline work).

Preferred Skills

• Technology- Architecture
• Technology- Infrastructure-Transformation
• Foundational- Methodologies- Business Transformation
• Foundational- Quality Assurance
• Technology- Artificial Intelligence
• Foundational - Artificial Intelligence- Responsible AI by Design
• Foundational - Strategy- Advisory Skills
• Technology- Machine Learning- Generative AI- retrieval augmented generation (rag)
• Foundational- Quality Engineering- Quality Engineering Strategy Design
• Technology- Agentic AI- Agent Engineering
• Technology- Agentic AI- AgentOps