Forward Deployed Engineer - New Grad

About the role

Chalk (chalk.ai) is the platform for production AI, trusted by enterprises such as Whatnot, Grindr, Mission Lane, Turo and Apartment List. Its Context Engine queries data across warehouses, databases, streams and APIs, and its runtime gives agents and models infrastructure and governed access to LLMs and tools. As a Forward Deployed Engineer, you will be embedded with customers' data engineering, data science and machine learning teams, writing code that connects Chalk to their infrastructure and use cases, and proving out new capabilities before building the first version into the platform. The position starts in Spring 2027.

Key responsibilities

• Write code across the entire codebase to implement Chalk technology for customers and prospects, becoming familiar with Chalk infrastructure and integrating it in different environments
• Discover customer needs and design, implement and ship new features
• Work closely with Engineering and Sales teams
• Act as the primary technical point of contact pre-sales and post-sales, including onboarding and supporting existing customers
• Recommend new products as customers' businesses evolve
• Help interview and grow the Engineering team

Required profile

• Bachelor's degree in Computer Science or equivalent
• Professional backend software engineering experience
• Ability to collaborate in teams of technical and non-technical people
• Excellent written and verbal communication, problem-solving, storytelling and analytical skills
• Experience working closely with sales teams and customers is a plus

Required skills

• Technical background including experience writing software or building ML models
• Proficiency in Python and SQL
• Bonus: previous experience with ML/data products or services, understanding of MLOps/infrastructure, or prior forward-deployed engineer experience in a high-growth ML startup

The company is in the office five days a week; travel to customer sites is rare because the engineer supports teams from multiple customers while working in the office.