Deepchecks is looking for an AI Solutions Engineer who combines technical expertise in AI/ML systems with strong business acumen and communication skills. This role bridges the gap between cutting-edge AI technologies and real-world business needs—requiring someone who can design, implement, and deliver pinpoint AI solutions, accurate for the customers' needs, while guiding them in extracting maximum value from our system.

About the Role

As an AI Solutions Engineer, you’ll partner with enterprise clients to understand their challenges and architect AI-driven solutions using the Deepchecks platform. You’ll collaborate with leading data science and ML engineering teams, working alongside experienced practitioners to ensure smooth adoption and measurable business outcomes.

You’ll design and deliver proofs of concept, lead workshops, and build compelling demos showcasing the capabilities of Deepchecks for AI evaluation, monitoring, and reliability. Acting as the key interface between our product, research, and customer teams, you’ll help translate technical requirements into impactful AI solutions.

Required Qualifications

• B.Sc. in Computer Science, Engineering, Data Science, or a related quantitative field.
• 3+ years of experience in AI/ML engineering, solutions engineering/architecture, or related technical roles.
• Hands-on experience with modern AI/ML workflows, including large language models (LLMs), MLOps, or production-grade model deployment.
• Proven track record of engaging with enterprise customers, including pre-sales activities (demos, PoCs, workshops).
• Strong software engineering and/or data engineering fundamentals (e.g., APIs, cloud services, data pipelines).
• Ability to work independently while managing multiple client-facing projects.
• Excellent communication skills, with the ability to explain complex AI concepts to both technical and business stakeholders.
• Customer-first mindset, with a focus on delivering practical, value-driven AI solutions.

We're looking for someone who:

• Values real-world impact and scalable solution delivery over purely theoretical work.
• Balances technical depth with business pragmatism.
• Can own projects end-to-end while staying aligned with cross-functional teams.
• Identifies opportunities to create value through AI and articulates them clearly to clients.
• Thrives in a dynamic, customer-facing role at the intersection of AI innovation and business adoption.