Careers @ Ease Vertical AI, Inc.

We're Hiring Two Technologists As Founding Team Members!

Are you an Applied ML Engineer or a Full-Stack Enterprise AI Product Developer?

This is your chance to shape the future of work and potentially become our future CTO!

Why Join Us?

• Impact: Build AI-powered solutions that transform industries.

• Ownership: Substantial stock options in an early-stage, high-growth startup.

• Compensation: $120K-$150K base salary (initially with minimal benefits).

• Growth: Salaries, benefits, and valuations will increase with company success.

• Leadership: Opportunities to evolve into a technical leadership role.

• Mentorship: Learn from founders, investors, and industry veterans.

• Culture: Work in an innovative, collaborative, and diverse environment.

About Us

• At Ease Vertical AI, we believe Generative AI’s true power lies in solving specialized, high-value vertical challenges. Our mission is to deliver easy-to-deploy, agent-based Generative AI solutions that streamline complex workflows, integrate multimodal data, and capture tribal knowledge to enhance productivity and efficiency.

• Our team, advisors, and investors have led AI/ML innovations at IBM, Intel, OpenAI, Meta, Google, Databricks, Oracle, and more.

• Pre-seed funded by an angel investor with a track record of building and exiting a global cloud platform.

• Our first product (stealth mode) targets a multi-hundred-billion-dollar vertical, transforming how businesses create value.

The Opportunity

As one of our two founding team members, you will be instrumental in defining and executing our product vision. Further, one of you will have the opportunity to become our future CTO.

Role 1: As a Full-Stack Enterprise AI Product Engineer, you will:

• Architect and build full-stack solutions with cutting-edge AI-driven user experiences.

• Develop scalable and secure cloud-based enterprise products.

• Code intuitive workflows that simplify complex business processes.

• Integrate LLMs and multi-agent architectures into enterprise applications.

Role 2: As an Applied Machine Learning Engineer, you will:

• Design, build, and deploy multi-agent LLM solutions.

• Solve challenges like hallucinations, data privacy, inference cost, and latency.

• Implement robust MLOps pipelines for seamless deployment and monitoring.

• Leverage full-stack technologies to integrate the latest LLM and Agentic architecture innovations.

What We’re Looking For

Both roles require:

• Entrepreneurial mindset with a sense of ownership and drive to create impact from scratch.

• Hands-on experience designing, building (coding), and deploying AI-powered enterprise products.

• Curiosity to work with the latest LLM and multi-agent system innovations.

• Collaboration and empathy in working and proactively communicating with teams and customers.

• Industry experience delivering commercial AI products beyond just internships and academic projects.

Role 1: Full-Stack Enterprise AI Product Engineer Qualifications

• 4+ years designing and developing scalable cloud-based full-stack solutions.

• Proficiency in React, Node.js, Python, and cloud platforms (AWS, GCP, Azure).

• Experience with AI-powered UX, databases (SQL, NoSQL), and LLM integration.

Role 2: Applied Machine Learning Engineer Qualifications

• 2+ years developing AI/ML solutions leveraging LLMs and multi-agent frameworks.

• Expertise in LLM fine-tuning, API integration, retrieval-augmented generation (RAG).

• Strong MLOps experience deploying, scaling, and monitoring AI models.

• Experience integrating AI/ML models into full-stack enterprise applications.

How to Apply

Email us at engage@easeverticalai.com with:

• Your resume (include dates and locations for each work experience).

• A cover letter detailing:

• Your visa/work permit status for full-time work in the U.S.

• Your career goals and why this role excites you.

• What makes you uniquely qualified for our founding team.

Important Details

• Work Authorization: At this stage, we can only consider candidates authorized to work long-term in the U.S. (U.S. citizens, Green card holders).

• Location: Preference for Pacific Time Zone candidates, with a strong preference for those based in the San Francisco Bay Area.

• Diversity: We embrace diverse perspectives and welcome applicants from all backgrounds.

• Recruiters & Outsourced Developers: Currently, we're unable to engage external recruiters or outsourced development teams.