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About the Role
We are seeking a highly skilled and strategic Business Development Executive III to join the AI Business Unit supporting new and exciting AI vendors and NeoCloud providers. This role requires spending 50% or more of your time in the field, interacting with customers and vendors. As a Business Development Executive III, you will be responsible for creating and maintaining customer relationships, with a strong focus on providing value\-added solutions. You will develop and maintain the business relationship by providing solutions for defined account(s) in a product line, to achieve the identified strategy and business financial objectives.
What You’ll Do
- Responsible for the execution of the strategic customer growth plans and business relationships in assigned account(s) by providing value added solutions.
- Delivers sales results for TD SYNNEX by both organically growing business within their assigned strategically large focus customers and in successfully closing large multi\-year sales proposals.
- Executing against vendor initiatives and serving as a subject matter expert (SME) on assigned vendors brand, technology solutions, and program offerings for our customers.
- Maintains and drives trending knowledge of products, competitors, technology and customers in the assigned supplier product market
- Attend events as a representative of both the company and the vendor, including but not limited to; Industry events, Reseller\-sponsored events (end user facing), Distribution events, Vendor\-sponsored events (reseller facing)
- Creating reports and presentations and delivering group and management presentations at customer sites.
- Able to speak to the customer on TD SYNNEXs High\-Growth value propositions, including Cloud, Data, IoT, etc.
- Identifying and creating opportunity demand for products, coordinating seminars, training, and resource awareness for assigned customers to drive growth.
- Performing analysis and reporting results of various program impact for identified customers, communicating success, issues, and future growth plan strategies to the Account Manager.
- Mastery knowledge of assigned Vendor’s products/services as well as those of the entire organization. Fluidly move amongst products/services and be equally effective. Full understanding of TD SYNNEX’s strategic sales pillars and associated value offerings to effectively sell into the territory
- Works on a cross\-section of the largest and/or most important accounts with the highest degree of complexity and variability. The Vendor Field BDE III territory is the more advanced in financial nature; as to company impact / benefit (annual revenue, gross profit and/or complexity dynamics).
- Maintaining up\-to\-date knowledge of products, competitors, technology, and customers in the assigned supplier product market.
- May coach and develop more junior team members.
What We’re Looking For
- 8 years of sales experience required.
- Bachelors degree or equivalent experience required.
- Thorough knowledge of solutions and assigned products.
- Ability to deliver strategic vendor solutions and identify new partners.
- Established relationships with key vendor contacts.
- Proficient in communication, negotiation, and collaboration.
- Strong organizational and time management skills.
- Strong leadership skills with a willingness to lead and innovate.
- Ability to work independently and multitask effectively.
- Comfortable with technology and basic office tasks.
- Willingness to travel and occasionally work non\-standard hours.
- Remote/work\-from\-home capability.
At TD SYNNEX, our values guide everything we do: Together, We Own It, We Dare to Go, We Grow and Win, and above all, We Do the Right Thing. These principles shape how we work with each other, our partners, and our communities as we drive innovation and create lasting impact.
What’s In It For You?
- Elective Benefits: Our programs are tailored to your country to best accommodate your lifestyle.
- Grow Your Career: Accelerate your path to success (and keep up with the future) with formal programs on leadership and professional development, and many more on\-demand courses.
- Elevate Your Personal Well\-Being: Boost your financial, physical, and mental well\-being through seminars, events, and our global Life Empowerment Assistance Program.
- Diversity, Equity Inclusion: It’s not just a phrase to us; valuing every voice is how we succeed. Join us in celebrating our global diversity through inclusive education, meaningful peer\-to\-peer conversations, and equitable growth and development opportunities.
- Make the Most of our Global Organization: Network with other new co\-workers within your first 30 days through our onboarding program.
- Connect with Your Community: Participate in internal, peer\-led inclusive communities and activities, including business resource groups, local volunteering events, and more environmental and social initiatives.
Don’t meet every single requirement? Apply anyway.
At TD SYNNEX, we’re proud to be recognized as a great place to work and a leader in the promotion and practice of diversity, equity and inclusion. If you’re excited about working for our company and believe you’re a good fit for this role, we encourage you to apply. You may be exactly the person we’re looking for!
We are an equal opportunity employer and committed to building a team that represents and empowers a variety of backgrounds, perspectives, and skills. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, gender, gender identity or expression, sexual orientation, protected veteran status, disability, genetics, age, or any other characteristic protected by law.
TD SYNNEX is an E\-Verify company
Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 3,708 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At TD SYNNEX, this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills in Demand for This Role
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $216,175 based on 270 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
TD SYNNEX AI Hiring
TD SYNNEX has 1 open AI role right now. They're hiring across AI Product Manager. Based in Greenville, SC, US.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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