Full-Time
Director of Applied AI
Omnifold
11-50 employees
AI-driven supply chain forecasting and optimization
No salary listed
San Francisco, CA, USA + 1 more
More locations: New York, NY, USA
In Person
The posting also lists the East Coast generally as an on-site location.
 Sales & Account Management (1) |
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- 10+ years of experience in technical sales or consulting, such as sales engineering, forward-deployed engineering, or solution architecture.
- Prior experience as a data scientist or selling a product that required a foundational understanding of machine learning.
- Experience supporting complex, high-value enterprise sales cycles.
- Excellent project management skills and attention to detail.
- Experience using Python and SQL to answer complex questions and solve business problems.
- Strong business intuition paired with technical rigor.
- A hands-on builder mindset and willingness to learn new technologies and topics as needed.
- Confidence engaging with business and technical stakeholders.
- Core data analysis and machine learning skills.
- An example demonstrating how artificial intelligence, machine learning, or optimization was used to solve a business problem.
- Engage directly with customer problems to understand data and operational challenges.
- Frame customer problems clearly.
- Lead technical and value-oriented demonstrations for technical and non-technical stakeholders.
- Work hands-on with data using Python and SQL.
- Build custom demonstrations and prototypes to support go-to-market activities.
- Act as a trusted technical partner during evaluations, pilots, and implementations.
- Support active customer deployments to ensure the platform's value is fully realized.
- Create a demonstration in the application and present it to the team.
Omnifold.ai uses artificial intelligence to help large and fast-growing brands and multinational companies manage supply chains and investment decisions. Its AI systems analyze data to predict demand and optimize plans for inventory, production, procurement, logistics, and marketing. The company relies on self-improving AI that learns from new data to improve forecasts and recommendations over time. By giving organizations better visibility and forward-looking guidance, Omnifold.ai aims to reduce waste, lower costs, and improve reliability in supply chains and investment outcomes. The goal is to help clients anticipate future needs, make smarter choices, and execute plans more effectively in a complex global market.
Company Size
11-50
Company Stage
N/A
Total Funding
N/A
Headquarters
N/A
Founded
2024
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Simplify's Take
What believers are saying
- Omnifold closed a $300M Series B on June 26, 2026, backed by Kleiner Perkins.
- Not Your Mother's Hair Care cited Omnifold's forecasts beating shipments in a recent pilot.
- Demand-planning buyers are shifting from reactive to proactive AI, expanding budget for forecasting tools.
What critics are saying
- The company still lists only 15 employees, limiting enterprise delivery, support, and sales scale.
- Omnifold's customer proof remains thin; public evidence centers on pilots and case studies, not logos.
- Series B pressure after June 2026 funding demands rapid growth or investor disappointment by 2027.
What makes Omnifold unique
- Omnifold sells purpose-built AI planning, not generic chatbots, for supply-chain forecasting and optimization.
- Its platform learns each customer's network, ingesting internal and external signals for granular decisions.
- Recent case studies show SKU-level gains: 64% over-forecast improvement and 25% revenue lift.
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6 month growth
↓ -17%1 year growth
↓ -17%2 year growth
↓ -17%What Not Your Mother's haircare is prioritizing in 2026. In a recent CGT webinar Eric Falkenmayer, Senior Manager of Demand Planning at Not Your Mother's Hair Care, shared how critical trends in AI are playing out inside a fast-growing CPG brand, and where he sees the biggest opportunities ahead. CGT's latest supply chain report paints a clear picture: consumer goods manufacturers are moving from reactive to proactive stand regarding AI, and AI-powered demand forecasting is at the center of that shift. With 53% of companies planning major AI and machine learning upgrades in 2026, the question is no longer whether to adopt, it's how to apply these tools quickly where they'll drive the most value. From Reactive to Proactive When asked about the single most critical priority for supply chain leaders heading into 2026, Eric was direct: it's the shift from reacting to disruptions to making data-driven decisions ahead of them. That means connecting internal data like shipments, POS, CRM and inventory positioning with external signals and using purpose built AI to plan at a speed and scale. The "Holy Grail" of Demand Forecasting For Eric, the highest-value application of AI isn't strictly incremental accuracy gains on the base business. It's forecasting for innovation: new SKU launches, new customer expansions, and new channels where historical comps are limited. He called it "the holy grail of demand forecasting" and pointed to a recent pilot with Omnifold where forecasts based on their purpose built AI tracked significantly closer to actual shipments than the team's original projections using the same underlying data. Purpose-Built Over General-Purpose A recurring theme was the importance of choosing AI tools designed for the specific problem at hand. Eric drew a sharp distinction: a large language model like ChatGPT is built for conversation, and autonomous driving AI is built to navigate roads safely: you wouldn't swap them. Supply chain forecasting demands the same purpose built approach. Alignment between a tool's design and the problem it solves was a key factor in Not Your Mother's decision to partner with Omnifold. Watch the Full Conversation To hear Eric's full perspective including a detailed walkthrough of Demert's IBP process and a discussion on AI adoption gaps and sustainability visit and subscribe to the Omnifold YouTube channel.