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Job Function: Sales The role: Job Summary
SoftwareOne is seeking a quota\-carrying Data, AI \& Workforce Modernization Solution Sales Specialist to join its Multi‑Vendor Solutions team, reporting to the ISV Alliance Director. This role helps customers modernize data platforms, prepare for AI adoption, transform digital workplaces, and improve workforce productivity through outcome\-based, vendor\-agnostic solutions. Role \& Responsibilities* Own pipeline, revenue, and gross profit targets.
- Generate and advance net\-new opportunities.
- Lead customer discovery and solution strategy discussions.
- Develop executive\-level business cases and ROI recommendations.
- Recommend vendor\-agnostic solutions aligned to customer goals.
- Partner with Account Managers and Services teams through the sales lifecycle.
- Build ecosystem partner relationships.
- Maintain forecasting and CRM hygiene.
- Travel 20% required
What we need to see from you: What you offer* 3\+ years of relevant sales, consulting, engineering, architecture or business development experience.
- Proven record of quota attainment and revenue growth.
- Experience leading customer\-facing discussions with technical and business stakeholders.
- AI Readiness \& Adoption
- Data Governance \& Modernization
- Analytics \& BI
- Digital Workplace Transformation
- End User Computing
- VDI
- Collaboration \& Content Governance
- Migration \& Tenant Consolidation
- Application Modernization
- Experience building ROI analyses and executive presentations.
- Excellent communication and stakeholder management skills.
- CRM forecasting experience.
- Vendor certifications preferred.
*The preceding job profile has been designed to indicate the general nature and level of work performed by associates within this role. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities, and qualifications required. Additional duties may be assigned and may be subject to change at any time due to reasonable accommodation or other reasons.* Success Criteria* Consistently meets or exceeds assigned pipeline, revenue, and gross profit targets.
- Builds a strong pipeline through discovery, workshops, assessments, and partner programs.
- Delivers measurable customer outcomes while driving partner\-influenced revenue growth.
Organizational Alignment* Reports to: ISV Alliance Director
- Collaboration with Account Managers, Solution Sales and delivery SMEs
What we offer
- Generous pay with bonus structure (quarterly or bi\-annual depending on the role)
- Independent environment without a lot of red tape where you are empowered to make decisions
- Substantial benefits package that includes:
- Full suite of medical coverage with A\+ carriers, Dental, and Vision with strong employer contributions plus additional voluntary coverage available for Pets, Identity Theft Protection, Accident \& Critical Illness
- 401k program with employer matching 50% up to the first 10% of employee’s contributions
- Wellness plan that includes credits to premiums and employer contributions towards the savings plan of your choice
- Access to EAP and concierge services plus pre\-paid legal at no cost
- Abundant time off that includes paid holidays, floating holidays, your birthday off, a volunteer day, and discretionary time off (DTO)
- Employee stock purchase plan
- Learning and development opportunities galore, tuition reimbursement, and much more!
- Specific to Nashville\-based office employees: company\-paid parking.
- Winning culture, inclusive environment, and friendly people all over the world
- A remote\-friendly organization, with colleagues working remotely either part or full\-time
Target compensation for this role will be $120\-140K USD (mix of base salary and bonus). Actual offers may be higher or lower than this range and will be determined based on a variety of factors, including (but not limited to) candidates’ qualifications, experience, education, and work location.
We are not able to consider candidates residing in the state of Hawaii currently.
Why SoftwareOne?:
SoftwareOne is a global provider of software and cloud solutions. With a presence in over 70 countries and more than 12,000 professionals, we help organizations optimize software investments, modernize applications, and unlock the value of cloud, data, and AI.
Our people are at the core of everything we do. We enable collaboration across borders, continuous learning, and opportunities to grow in a fast\-evolving technology landscape. Whether your focus is on technology, customer success, or business operations, your ideas matter, and your contributions make a difference.
Join a global team where you can build your skills, work with leading technologies, and make a real impact for our customers.
Accommodations:
SoftwareOne welcomes applicants from all backgrounds and abilities to apply. If you require reasonable adjustments at any point during the recruitment process, email us at [email protected]. Please include the role for which you are applying and your country location. Someone from our organization that is not part of the decision\-making process will be in touch to discuss your specific needs, and we will make every effort to accommodate you. Any information shared will be stored securely and treated in the strictest of confidence in line with GDPR.
At SoftwareOne, we are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants and teammates without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. Additionally, we encourage experienced individuals that have taken an intentional career break and are now prepared to return to work to explore our SOAR program.
Salary Context
This $120K-$140K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $180K across 1841 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At SoftwareOne, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $218,750 based on 3,817 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($130K) sits 41% below the category median. Disclosed range: $120K to $140K.
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.
SoftwareOne AI Hiring
SoftwareOne has 2 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Nashville, TN, US, US. Compensation range: $140K - $165K.
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/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
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).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
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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