Interested in this AI Product Manager role at AthenaSoft?
Apply Now →About This Role
Location: Dallas–Fort Worth, TX (Preferred) \| Texas Remote Considered
Engagement Type: Independent Contractor (1099\)
Compensation: Monthly Retainer \+ Uncapped Commission (Target On\-Target Earnings: $100,000\+)
About Auxiliobits
Auxiliobits is a US\-based AI and Automation consulting company helping enterprise organizations transform Finance, Shared Services and business operations through Agentic AI, Intelligent Automation, Process Automation and Enterprise AI solutions.
Our clients include global organizations across Finance, Manufacturing, Healthcare and Shared Services. We help organizations reduce manual work, improve operational efficiency and accelerate digital transformation without replacing their existing ERP investments.
As part of our US growth strategy, we are expanding our business development presence and are looking for an experienced Enterprise Business Development Manager to help accelerate enterprise growth across North America.
About the Role
This is a strategic business development role for someone who enjoys building executive relationships and creating new enterprise opportunities.
This is not a transactional sales or high\-volume cold\-calling position.
You will work directly with the Founder to identify target accounts, engage senior decision\-makers, develop qualified opportunities and help shape Auxiliobits' US go\-to\-market strategy.
You should enjoy opening doors into enterprise organizations and building long\-term relationships with executive stakeholders.
What You'll Do
- Develop new enterprise business opportunities across the United States.
- Build relationships with CFOs, CIOs, Shared Services Leaders, Finance Transformation Leaders, Operations Executives and Digital Transformation leaders.
- Identify and pursue target enterprise accounts through strategic outbound prospecting, networking and referrals.
- Generate qualified discovery meetings and sales opportunities.
- Develop account plans for named enterprise prospects.
- Attend industry events, executive networking opportunities and customer meetings.
- Work closely with the Founder during discovery sessions, solution discussions and proposal presentations.
- Maintain an active sales pipeline and CRM.
- Provide market feedback to help refine Auxiliobits' service offerings and go\-to\-market strategy.
Who We're Looking For
You are someone who enjoys creating opportunities rather than waiting for them.
You have a consultative approach to enterprise sales and understand how to build credibility with executive decision\-makers.
You are comfortable representing a boutique consulting company and working closely with leadership to win strategic enterprise accounts.
Required Experience
- 7\+ years of enterprise B2B business development or enterprise sales experience.
- Demonstrated success selling technology consulting, enterprise software, automation, AI, ERP or digital transformation solutions.
- Experience selling into mid\-market or enterprise organizations.
- Proven ability to originate and develop new business opportunities.
- Strong executive communication and presentation skills.
- Ability to work independently with minimal supervision.
- Willingness to travel for client meetings, networking events and conferences.
Preferred Experience
Experience selling one or more of the following:
- Intelligent Automation
- Agentic AI
- Robotic Process Automation (RPA)
- Enterprise AI
- ERP Consulting
- Finance Transformation
- Shared Services Transformation
- Digital Transformation
- Enterprise Technology Consulting
Experience with organizations such as Fortune 1000 companies, Global Business Services (GBS), Shared Services Centers (SSC) or large enterprise operations is highly desirable.
This Role Is Not For
This opportunity is unlikely to be a good fit if your experience has primarily been in:
- Retail or consumer sales
- Insurance
- Telecommunications
- Automotive sales
- Residential real estate
- Door\-to\-door sales
- Appointment\-setting or SDR\-only roles without enterprise account ownership
Compensation
- Monthly consulting retainer
- Attractive uncapped commission structure
- Target On\-Target Earnings (OTE): Approximately $100,000\+ annually
- Significant upside for strong performers who consistently generate and close enterprise business
Why Join Auxiliobits?
This is an opportunity to become a key part of a growing AI and Automation consulting company focused on enterprise transformation.
You will work directly with the Founder, influence our US growth strategy and help build long\-term relationships with enterprise organizations across North America.
If you enjoy consultative selling, creating new opportunities and helping enterprise clients solve meaningful business challenges through AI and automation, we'd love to hear from you.
Application Questions
As part of your application, please answer the following:
- Describe the largest enterprise account you personally originated and helped close. What was the approximate contract value, and what was your role in winning the business?
- Which industries have you sold into? (Finance, Manufacturing, Healthcare, Shared Services, Technology, Logistics, Other)
- Have you sold technology consulting, enterprise software or digital transformation solutions to enterprise organizations?
- Are you comfortable working as an independent contractor (1099\) with a monthly retainer and uncapped commissions?
- Why do you believe your experience makes you a strong fit for helping Auxiliobits grow its enterprise client base in the United States?
Pay: $90,000\.00 \- $130,000\.00 per year
Work Location: Hybrid remote in Dallas\-Fort Worth, TX
Salary Context
This $90K-$130K range is in the lower quartile for AI Product Manager roles in our dataset (median: $188K across 140 roles with salary data).
View full AI Product Manager salary data →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 AthenaSoft, 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. This role's midpoint ($110K) sits 49% below the category median. Disclosed range: $90K to $130K.
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.
AthenaSoft AI Hiring
AthenaSoft has 1 open AI role right now. They're hiring across AI Product Manager. Based in Dallas-Fort Worth, TX, US. Compensation range: $130K - $130K.
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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