AI Engineer

Field Materials develops AI-native construction procurement software. Our AI agents automate workflows in procurement, AP, and inventory management. As a result, our customers spend less time on data entry and manual workflows in legacy ERPs. Our edge is in best-in-class AI and powerful integrations with existing construction ERPs.

We're post-PMF and scaling: already processing $3B+ in material purchase volume across 16 construction trades.

Tech Stack:

• Generative AI + optimization algorithms drive document extraction. Models are heavily tuned for the domain. Algorithms, LLMs, and RAGs drive automations. Strong metric-oriented culture with evaluation sets across the board.
• Go, GraphQL & Postgres (gqlgen, pgx, squirrel, dataloaders). Sophisticated data models aligned with ERPs. Complex authorization and approvals. In-house observability for GraphQL. AWS stack: ALB, ECS, RDS, S3.
• Bidirectional integrations with unified data model across 13+ construction systems & on-prem connector. REST APIs, ODBC, COM, and others.
• We spin out separate services where it makes sense. The construction data model is complex with a lot of business data constraints so we use ACID transactions whenever possible.

We’re looking for AI engineers who want extreme ownership. You’re not just a research scientist; you own models, data pipelines, evaluation suites, and AI product features.

About You:

• You are excited about startups and new products.
• You enjoy solving complex problems and iterating fast.
• You realize that products are built iteratively and specs evolve with customer feedback.
• You care about system and code design: well architected code is easier to understand, refactor, evolve, and inherit.
• You enjoy optimizing AI-enabled features to automate tedious work with high financial impact for customers.
• You prefer well thought-out, scientific solutions.

What We Look For:

• BS (or higher) in Mathematics, Computer Science, or related technical field.
• 2-5+ years of production level experience in Backend Engineering or AI Engineering.
• Experience in designing, evaluating and integrating AI models and data pipelines.
• Experience with document data extraction problems.
• Experience working with SQL databases and complex data models.
• Strong foundation in algorithms and data structures and their real-world use cases.
• Proficiency with Golang is a nice-to-have.

Benefits:

• Flexible time off
• Equity awards
• Gym reimbursement
• Personal development fund for books, courses, certifications and conferences
• Swanky new MacBook Pro
• Work headphones reimbursement
• Annual offsites at fun locations across Europe