Senior Manager - Enterprise AI Transformation at QAD, Inc.

Pune, maharashtra, India -

Full Time

Start Date

Immediate

Expiry Date

07 Sep, 26

Salary

0.0

Posted On

09 Jun, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI Transformation, Enterprise Automation, Digital Transformation, Product Management, Technology Strategy, Governance Model, Reference Architecture, Value Capture, Stakeholder Management, Data Architecture, Workflow Automation, Agentic AI, Risk Management, Operating Model Design, Strategic Prioritization, Executive Communication

Industry

Software Development

Description

Company Description QAD is a leading provider of adaptive, cloud-based enterprise software and services for global manufacturing companies. At QAD, we help customers transform and innovate through modern cloud platforms, data-driven insights, and AI-enabled solutions. Our Engineering organization plays a critical role in delivering resilient, scalable, and high-quality platforms that power customer success worldwide. Job Description The Senior Manager - Enterprise AI Transformation will lead the internal AI leverage agenda across QAD by translating company-level productivity goals into a governed, prioritized, and measurable AI transformation roadmap. The person will own the overall operating model for internal AI adoption: prioritization, governance, reference architecture coordination, usage controls, value tracking, and execution cadence. They are not a PMO lead. They are the person who ensures AI moves from fragmented functional experimentation into scalable, governed execution. Key responsibilities Enterprise AI leverage roadmap Own the enterprise internal AI leverage roadmap across functions and BUs. Prioritize use cases based on value, feasibility, functional readiness, data readiness, and risk. Translate executive priorities and external diagnostic outputs into executable implementation waves. Maintain a clear view of what is already underway, what should be accelerated, what should be stopped, and what requires leadership decision. Governance and operating model Define the internal AI governance model in partnership with IT, Data, Engineering, InfoSec, Legal, Procurement, and functional leaders. Establish use-case intake, prioritization, approval, and escalation processes. Create a risk-tiered governance approach: fast-track low-risk use cases, structured review for medium-risk use cases, and formal approval for high-risk / sensitive-data use cases. Ensure the team enables adoption without becoming a bureaucratic PMO. Reference architecture and AI stack coordination Coordinate the internal AI reference architecture across approved tools, data sources, enterprise systems, workflow layers, and governance controls. Work with IT/Data/Engineering to define standard patterns for connecting AI tools to systems and datasets. Help define when QAD should buy, configure, integrate, or selectively build. Prevent fragmented functional AI stacks and unmanaged shadow AI deployments. Usage, access, and spend controls Define operating controls for tools such as Claude, Gemini, ChatGPT Enterprise, BigQuery, Workday AI, Salesforce/Agentforce, Glean, and other internal AI capabilities. Establish usage tracking across users, functions, use cases, tokens/credits, spend, and adoption. Partner with Finance and IT to manage spend, license allocation, and value-for-money. Ensure access rights, data permissions, and restrictions are aligned with InfoSec and data governance requirements. Delivery and value capture Track delivery progress, adoption, productivity impact, financial value, and risks across the AI leverage portfolio. Define standard metrics for each initiative: baseline, target, adoption, usage, productivity, quality, cycle time, and financial impact. Prepare leadership updates, decision materials, and board-ready summaries where needed. Ensure pilots have clear success criteria and can either scale, pivot, or be shut down quickly. Team leadership Lead Functional AI Enablement Leads and AI/Data Integration Engineers. Set standards for workflow design, agent requirements, documentation, testing, adoption, and value tracking. Coach the team to operate as hands-on execution partners, not meeting schedulers or project-plan chasers. Qualifications Required Qualifications 8-15+ years of experience in digital transformation, AI transformation, enterprise automation, product management, technology strategy, operations transformation, or consulting. Experience working across business and technology teams. Strong understanding of enterprise systems, data architecture, workflow automation, and AI/agentic tools. Able to work directly with CFO, CHRO, COO, CRO, Engineering, IT, and functional leaders. Strong enough to challenge functions constructively. Pragmatic build-vs-buy mindset. Comfortable with ambiguity, executive communication, and measurable value capture Additional Information Qualification Your health and well being are important to us at QAD. We provide programs that help you strike a healthy work-life balance. Opportunity to join a growing business, launching into its next phase of expansion and transformation. Collaborative culture of smart and hard-working people who support one another to get the job done. An atmosphere of growth and opportunity, where idea-sharing is always prioritized over level or hierarchy. Compensation packages based on experience and desired skill set About QAD: QAD | Redzone is redefining manufacturing and supply chains through its intelligent, adaptive platform that connects people, processes, and data into a single System of Action. With three core pillars — Redzone (frontline empowerment), Adaptive Applications (the intelligent backbone), and Champion AI (Agentic AI for manufacturing) — QAD | Redzone helps manufacturers operate with Champion Pace, achieving measurable productivity, resilience, and growth in just 90 days. QAD is committed to ensuring that every employee feels they work in an environment that values their contributions, respects their unique perspectives and provides opportunities for growth regardless of background. QAD’s DEI program is driving higher levels of diversity, equity and inclusion so that employees can bring their whole self to work. We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class. Department: Technology Location: India - Pune - Adjunct 0ffice

Responsibilities

Lead the internal AI transformation roadmap by translating productivity goals into a governed and measurable execution plan. Manage the operating model for AI adoption, including governance, reference architecture coordination, and value tracking across business units.