Senior AI Product Manager, webAI
Customer Engagement
Enterprise grade local AI applications
Be an early applicant
Enterprise grade local AI applications
101-200 employees
Be an early applicant
101-200 employees
Company mission
To revolutionize the AI industry by laying the foundation for the development of Super Intelligence (SI).
Role
Who you are
- 5+ years of Technical Product Management or Solution Architecture experience
- 2+ years specifically shipping AI, ML, Search, or Data products to production
- Deep Technical Fluency: You can explain the difference between vector search and keyword search, or why a specific prompt strategy is failing. You are comfortable reading technical papers or API docs
- Proven "Zero-to-One" Execution: Experience taking a product from a loose concept to a live deployment with real users
- Client-Facing Maturity: Experience navigating complex stakeholder landscapes; you can say "no" to a customer feature request by explaining the technical trade-offs clearly
- Data-Driven: Proficiency with evaluation frameworks; experience defining "ground truth" datasets
What the job involves
- We are looking for a Senior AI Product Manager to drive our Customer Engagement vertical. You will be bridging the gap between ambiguous customer problems and rigorous value delivery. While our research teams push the boundaries of distributed AI, your role is to ensure that when we engage with a customer, we build the right thing the first time
- You will own the discovery process that produces clarity, allowing our engineers to focus on building rather than guessing. You will define the "Evaluation Contract" before a single line of code is written and partner with AI engineers to select the best technical approach (e.g., Prompt Engineering vs. RAG vs. Fine-tuning) for the specific job-to-be-done
- At the Senior level, you are not just executing discovery; you are defining how we scale the function. You will set the standard for "Problem Briefs" and "Evaluation Contracts" that the rest of the organization follows
- Own the Discovery Process: Lead scoping to produce a Problem Brief for every engagement: the job-to-be-done, constraints, success criteria, and reliability expectations
- Define Evaluation Contracts: Define what data, metrics, and thresholds constitute success before building begins
- Partner on Technical Approach: Work with AI Engineers to determine the right tool for the job. You must be able to debate the trade-offs of RAG vs. Long-Context vs. Fine-tuning based on data, cost, and latency
- Extract & Standardize: Identify patterns in customer needs to surface platform gaps early; turn field learnings into engineering requirements
- Enable Focus: Your primary metric is clarity—reducing ambiguity so AI engineers can execute immediately without churning on requirements
- Synthesize Market Patterns: Look across multiple customer deployments to identify strategic platform gaps. You don't just report bugs; you propose architectural improvements to the core platform based on field evidence
Our take
On a mission to democratize artificial intelligence, WebAI has built a decentralized development platform that minimizes the amount of data required to build AI models. This directly challenges the assumption that big data is intrinsic to AI, and enables for local, ownable and customizable models to be made.
The company's unified execution layer helps to streamline the training and deployment of models in a way which is both scalable and flexible. Enterprises can use their existing infrastructure to run powerful models while ensuring their data never leaves their devices. Plus, they can tailor each model to their needs with no coding needed.
WebAI believes that off-the-shelf AI models lack the flexibility and control required to be used in real-world tasks, which is what its platform helps to combat. This approach has attracted impressive investment that will be used to grow its development efforts and elevate its mission to democratize AI.
Steph
Company Specialist at Welcome to the Jungle
Company
Funding (2 rounds)
Sep 2024
$60m
SERIES A
Dec 2022
$17m
SEED
Total funding: $77m
Company benefits
- Grow with us: Equity options so you share in our growth. Build your future as we build ours.
- Family first: Parental leave and fertility support for every stage of life. Your family matters here.
- Plan your future: A 401(k) to help you save and invest. Secure what's ahead with confidence.
- Stay well: Comprehensive health coverage for body and mind. Because balance fuels great work.
- Keep learning: A stipend to explore, study, and sharpen your skills. Growth never stops.
- Work anywhere: Remote-first with flexible time off to recharge. Find balance wherever you are.
Company HQ
Congress Avenue Historic District, Austin, TX
Leadership
David Stout
(Co-Founder & CEO)Alongside WebAI, David is the Founder of Ghost House Technology.
Ethan Baird
(Co-Founder & Chief Research Officer)Previously, Ethan was a Software Programmer at Ghost House Technology and a Web Technician at Revision Marketing and Design.
Tyler Mauer
(Co-Founder & Chief Innovation Officer)Tyler is also a Director of Product & Market at Ghost House Technology, Previously he held Consultant roles at YETi CGI, RANDY'S House, and Shinola.
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