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Executive Ai Strategy Jobs in Indiana (NOW HIRING)

Manager, Applied AI Strategy and Operations Job Purpose: As a Manager, Applied AI Strategy and ... Business Planning & Executive Storytelling: Build comprehensive segment analyses, growth models ...

... AI Strategy Director, you will lead the charge in developing innovative software solutions and ... You will make impactful decisions and oversee multiple projects, maintaining executive-level client ...

... , policies, processes, people, governance and partnerships, and translate program delivery into measurable business outcomes. Health & Life Science Program Executives are at the helm of AI and ...

... your business strategy--ready to get to work from day one. Our platform combines generative AI ... Enterprise Client Executive (Defend Account Management Team | Enterprise & Strategic Accounts ...

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Executive Ai Strategy information

What is the difference between Executive Ai Strategy vs Data Scientist?

AspectExecutive Ai StrategyData Scientist
Required CredentialsAdvanced degrees in AI, Business, or related fields; leadership experienceDegree in Computer Science, Data Science, or related fields; technical certifications
Work EnvironmentStrategic planning, cross-department collaboration, executive meetingsData analysis, model development, coding, and experimentation
Employer & Industry UsageTech companies, large enterprises, consulting firmsTech firms, finance, healthcare, research institutions

Executive Ai Strategy professionals focus on high-level AI implementation and strategic planning, working closely with leadership to align AI initiatives with business goals. Data Scientists, on the other hand, concentrate on technical data analysis, model building, and experimentation. While both roles require strong technical backgrounds, Executive Ai Strategy emphasizes leadership and strategic oversight, whereas Data Scientists focus on hands-on data work.

What are the key skills and qualifications needed to thrive as an Executive AI Strategist, and why are they important?

To thrive as an Executive AI Strategist, you need strong expertise in artificial intelligence, business strategy, and data analytics, typically supported by an advanced degree in a related field. Familiarity with AI platforms, data management systems, and certification in AI or machine learning frameworks (such as TensorFlow or AWS AI) is highly valuable. Exceptional leadership, strategic vision, and the ability to communicate complex technical concepts to non-technical stakeholders are essential soft skills. These capabilities ensure that organizations can effectively align AI initiatives with business objectives, driving innovation and competitive advantage.

How does an Executive AI Strategy role typically collaborate with other departments within an organization?

An Executive AI Strategy professional frequently works cross-functionally, partnering with leaders in IT, data science, operations, and business units to align AI initiatives with organizational goals. Collaboration often includes translating complex AI concepts into actionable business strategies, overseeing pilot projects, and ensuring ethical and responsible AI deployment. These professionals also facilitate communication between technical teams and executive leadership to drive adoption and maximize the impact of AI investments. Regular meetings, workshops, and joint planning sessions are common to ensure alignment and successful project execution.

What is an Executive AI Strategy role?

An Executive AI Strategy role involves leading the development and implementation of artificial intelligence strategies at an organizational or enterprise level. This executive oversees the integration of AI technologies to improve business outcomes, ensures alignment with company goals, and manages cross-functional teams to drive innovation. Responsibilities often include identifying opportunities for AI adoption, assessing risks, setting policies for ethical AI use, and staying updated with industry trends. The role requires a blend of technical knowledge, business acumen, and leadership skills to ensure successful AI transformation.
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Manager, Applied AI Strategy and Operations

Cloudera

Full-time

PTO

Posted 7 days ago


Job description

Business Area:

Corp. Strategy

Seniority Level:

Mid-Senior level

Job Description:

At Cloudera, we empower people to transform complex data into clear and actionable insights. With as much data under management as the hyperscalers, we're the preferred data partner for the top companies in almost every industry. Powered by the relentless innovation of the open source community, Cloudera advances digital transformation for the world's largest enterprises.

Job title: Manager, Applied AI Strategy and Operations

Job Purpose:

As a Manager, Applied AI Strategy and Operations within the Chief Business Officer and GM, Applied AI's organization, you will lead high-impact, global commercial and operational initiatives with a direct emphasis on accelerating Cloudera's Private AI growth.

Our Applied AI organization is a fast-moving, dedicated group of Forward Deployed Engineers (FDEs), Industry & Applied AI Specialists, and business strategy leaders committed to establishing Cloudera as the trusted standard for Private AI in the enterprise. In this high-autonomy, high-trust role, you will act as the strategic and analytical backbone behind our field engineering motions. You will prioritize the right initiatives across our strategic accounts, establish robust governance and operating rhythms, conduct deep-dive portfolio and sales pipeline analyses, and synthesize complex technical and commercial signals into actionable recommendations for Cloudera's senior leadership.

Key responsibilities:
  • Drive Global Governance & Operating Rhythms: Establish, evolve, and manage the programmatic operating rhythm for the global Applied AI organization across AMER, EMEA, and APAC. Lead the monthly business review (MBR) process-from metric gathering and CRM ingestion through deep quantitative analysis and executive synthesis for senior leadership.

  • Manage the AI Adoption Funnel: Partner with regional FDE and Applied AI Specialist leadership to track, analyze, and optimize customer progression through our four core execution stages: Discovery & Strategy, Solution & Value, Pilot & Prove, and Production & Scale.

  • Account Prioritization & Use Case Frameworks: Structure analytical frameworks grounded in real customer signal-joining technical discovery sessions, reviewing triage outcomes, and working directly with field engineering teams to filter and isolate high-ROI Private AI workloads. Conduct rigorous analyses to down-select and prioritize target accounts across our Top 100 strategic enterprise lists.

  • Define & Standardize Strategic Metrics: Collaborate with central Revenue Operations and AI GTM Sales Strategy to define, refine, and standardize key performance indicators around subscription and consumption-based Private AI adoption. Track organizational progress against critical milestones, including customer pitch meetings, on-site Use Case Workshops, Applied AI Hands-on Labs, and deployed production solutions.

  • Ecosystem & Commercial Strategy: Analyze and support go-to-market operational alignment with major AI infrastructure and ecosystem partners (including NVIDIA Blueprints and VAST). Evaluate revenue share models, joint sales plays, and co-deployment strategies to maximize platform pull-through and annual recurring revenue (ARR) expansion.

  • Cross-Functional Leadership & Solution Productization: Act as an embedded, highly trusted thought partner to technical and commercial leaders. Design and implement scalable processes for tracking team allocations and solution productization, ensuring repeatable delivery patterns are codified and communicated across Account Executives, Solution Engineers, and Professional Services globally.

  • Business Planning & Executive Storytelling: Build comprehensive segment analyses, growth models, and strategic business cases to support critical investment decisions, headcount planning, and resource allocation across regional pods.

Preferred Qualifications:
  • Strong problem-solving and structuring skills, with a proven ability to scope complex, ambiguous strategic challenges and identify root causes within technical go-to-market organizations.

  • Highly analytical and excellent at leveraging facts, CRM data, and customer insights to generate and validate strategic hypotheses regarding enterprise AI adoption and workload consumption.

  • Proven ability to communicate and build trust with stakeholders at all levels-including C-suite executives, technical engineering leaders, and regional sales VPs-by turning granular data and research into actionable insight and a well-structured executive storyline.

  • Deep familiarity with enterprise data management platforms, hybrid cloud architectures, data lakehouses (e.g., Apache Iceberg), and the broader AI/ML ecosystem capabilities.

  • Strong quantitative, financial modeling, and data manipulation skills; proficiency in GTM systems (e.g., Salesforce, Clari), business intelligence tools (e.g., Tableau, Power BI), and SQL is a strong plus.

  • Demonstrated capacity to operate with high autonomy in dynamic, fast-moving environments, building structure and operational rigor from the ground up rather than inheriting legacy processes.

Preferred Experience:
  • 6+ years of progressive work experience in sales strategy, revenue operations, business operations, or management consulting, with a demonstrated track record of driving cross-functional alignment and measurable business impact.

  • Direct experience supporting specialized technical sales, pre-sales, or post-sales delivery teams-particularly within Forward Deployed Engineering (FDE), Solution Architecture, or Applied AI Specialist organizations.

  • Deep domain experience in enterprise software, big data analytics, machine learning/AI, or hybrid cloud infrastructure companies.

  • Proven expertise working with cloud subscription, consumption-based (usage-driven), or product-led growth (PLG) business models, specifically tracking workload transition from pilot to production scale.

  • Experience supporting enterprise commercial or technical organizations through rapid 2-3x+ revenue growth periods and global expansion across AMER, EMEA, and APAC regions.

  • Note: Candidates without direct commercial ownership experience will still be strongly considered if they demonstrate long, deep tenure supporting commercial or technical sales leaders in a closely comparable enterprise GTM model.

  • The right person in this role has an opportunity to make a huge impact at Cloudera and add value to our future decisions. If this position has piqued your interest and you have what we described - we invite you apply!

  • This role is not eligible for immigration sponsorship.

The anticipated annual base salary range for this position is:

  • Washington: $144,000 - $180,000

  • New York: $144,000 - $180,000

  • California: $144,000 - $180,000

Individual compensation within the published range is determined by the candidate's skills, experience, qualifications, and primary work location. In addition to base pay, sales roles are eligible for Cloudera's commission plan, while non-sales roles are eligible for the corporate incentive plan. All employees receive a comprehensive benefits package

What you can expect from us:

  • Generous PTO Policy

  • Support work life balance with Unplugged Days

  • Flexible WFH Policy

  • Mental & Physical Wellness programs

  • Phone and Internet Reimbursement program

  • Access to Continued Career Development

  • Comprehensive Benefits and Competitive Packages

  • Paid Volunteer Time

  • Employee Resource Groups

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