Sell AI-driven solutions to mid-market businesses: prospect, qualify, consult with decision-makers, manage the full sales cycle, close deals, build long-term client relationships, and identify upsell opportunities with support from leadership and technical teams.
This is a commission-based role with unlimited earning potential. Top performers can expect significant payouts per deal closed. Our team is here to support your success with training, lead gen, and product expertise.
Dry Ground AI is helping companies transform their businesses with practical, next-generation artificial intelligence solutions. We work with mid-market business owners and executives to radically improve efficiency, automate processes, and create innovative customer experiences. Demand for real AI solutions is exploding, and we’re building a top-tier team to serve clients across industries.
Role Overview:
As an AI Solutions Sales Representative, you’ll play a vital role in connecting businesses with powerful AI solutions that drive growth and real results. You’ll identify and engage new business opportunities, consult with decision-makers, and guide clients through their AI adoption journey. You’ll enjoy high autonomy, flexible hours, and the chance to earn significant commissions for helping organizations succeed.
What You’ll Do:
- Prospect, qualify, and close new business for our suite of AI-driven solutions: delivering full-stack AI, automation, and end-to-end implementation throughout our clients’ businesses
- Consult with business owners and executives to understand needs and recommend tailored solutions
- Manage the full sales cycle from outreach to close, with marketing and technical support from our team
- Collaborate with leadership to refine messaging and capture new verticals
- Build long-term client relationships and identify upsell opportunities
What We’re Looking For:
- Proven experience in B2B sales (SaaS, consulting, tech, or agency background preferred)
- Consultative, entrepreneurial, and excited to learn new technology
- Excellent communication and relationship-building skills
- Self-motivated, goal-driven, and comfortable with a commission-based structure
- Strong organizational skills and ability to manage your own pipeline
What We Offer:
- Uncapped commission structure with industry-leading payout percentages
- Flexible/remote/fractional opportunity: build your pipeline on your schedule
- Support from a responsive leadership and technical team
- Access to compelling case studies, marketing materials, and product training
- The chance to get in early with a fast-growing AI solutions company
- Opportunity to have leads directed to you through our lead generation engine
If you’re motivated by growth, ownership, and making an impact in the world’s most exciting sector, we’d love to talk with you. Apply now to explore how you can shape the future of AI with us.
Similar Jobs
Fintech • Machine Learning • Payments • Software • Financial Services
Leads enterprise AI engineering strategy and multi-team delivery of scalable, responsible AI systems. Oversees foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, observability, and production optimization. Establishes responsible AI standards, makes technology decisions, develops long-term platform roadmaps, partners with research and risk teams, and attracts and mentors engineering talent.
Top Skills:
AWSAws UltraclustersAzureC#C++CudaGoGCPHugging FaceJavaPythonPyTorchVectordbs
25 Minutes Ago
Fintech • Machine Learning • Payments • Software • Financial Services
Leads data science for consumer and developer experiences, partnering with engineers and product managers to deliver customer-focused products. Builds, evaluates, validates, and deploys machine learning models using large-scale numerical and textual data. Applies statistical modeling, A/B testing, clustering, classification, sentiment analysis, time series, and deep learning while translating technical insights into business outcomes. The role also includes team leadership, talent development, and evaluating emerging AI and cloud technologies.
Top Skills:
SparkAWSCondaGenerative AiH2OMachine LearningPythonRRelational DatabasesScala
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Leads population health strategy, clinical innovation, care-model design, and evidence-based program development. Uses clinical, claims, and utilization data to identify intervention opportunities and evaluates products, partnerships, clinical guidelines, and care programs. Represents clinical perspectives with providers, health systems, clients, and executives while developing clinical talent. Requires an active medical license, board certification, clinical leadership, clinical practice, population health experience, strong analytics, and communication skills.
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory


