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About This Role
Company Overview
Xen.AI ( https://xen.ai/ ) is a global leader in Artificial Intelligence (AI) research and development, dedicated to transforming operations for financial institutions such as credit unions and community banks through innovative AI, Machine Learning, Deep Learning, Data Science, and fully managed SaaS solutions. Our mission is to empower our clients with cutting-edge digital transformation tools rooted in advanced data science.
Job Summary We are seeking a dynamic and strategic Head of Sales, Business Development & Marketing for AI solutions tailored to credit unions and community banks. This leadership role offers an exciting opportunity to spearhead growth initiatives, build strong client relationships, and lead cross-functional teams in a fast-paced, enterprise environment. The ideal candidate will be passionate about leveraging technology sales expertise to expand market presence and deliver impactful AI-driven solutions.
Compensation
Please note - For the 1st year all compensation would be 100% revenue based on the client projects that you would help to get and deliver.
After 1st year, based on company's progress we can consider formal corporate positions with market standard salary and equity etc.
Duties
- Develop and execute comprehensive sales strategies targeting credit unions and community banks to achieve aggressive growth objectives.
- Recruit, lead and manage a high-performing sales team, fostering a culture of excellence, accountability, and continuous improvement.
- Cultivate and maintain strong relationships with key decision-makers at client organizations through proactive outreach, presentations, and negotiations.
- Drive business development efforts by identifying new market opportunities, creating tailored proposals, and closing complex enterprise deals.
- Collaborate closely with marketing teams to develop targeted campaigns that elevate brand awareness and generate qualified leads.
- Utilize CRM systems such as Hubspot to track sales activities, analyze pipeline health, and generate insightful reports on sales performance.
- Provide executive-level reporting on sales metrics, market trends, and customer feedback to inform strategic planning.
Qualifications
- 10+ years of experience in doing consultative selling and professional services selling with Credit Unions and Community Banks.
- Proven experience in business development within the Credit Unions, Community Banks, Banking, Financial Services, Insurance sectors.
- Experience in selling Governance, Risk and Compliance (GRC) related solutions for community banks and credit unions.
- Proven success in outside sales, B2B sales, or enterprise selling within the financial technology sector or similar corporate environments.
- Extensive management experience leading sales or business development teams in SaaS or technology-driven markets.
- Strong background in marketing strategies combined with technical sales experience—particularly with AI or data science solutions for financial institutions.
- Proficiency with Hubspot CRM systems and sales management tools for analytics, reporting, and pipeline management.
- Exceptional customer relationship building skills with a focus on negotiation and deal closing at the executive level.
- Demonstrated ability to develop and implement effective sales strategies aligned with organizational goals.
- Excellent analysis skills to interpret market data, customer needs, and competitive landscape insights.
- Leadership qualities that inspire team development, cross-functional collaboration, and achievement of ambitious sales targets.
- Bachelor’s or Master's degree in Business, Marketing, or related field preferred.
- Authorized to work in United States, No H1B Visa or OPT sponsorship.
This role offers an inspiring platform for a motivated leader eager to shape the future of AI solutions within the financial services sector—empowering credit unions and community banks through innovative technology partnerships.
!!!! Please note that we do not work with any recruiters !!!!
Pay: $1.00 per year
Benefits:
- Flexible schedule
Work Location: Remote
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 9,079 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Xen.ai, 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 Required
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 $220,200 based on 947 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Xen.ai AI Hiring
Xen.ai has 3 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager. Based in Remote, US.
Remote Work Context
Remote AI roles pay a median of $188,000 across 2,316 positions. About 6% of all AI roles offer remote work.
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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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