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
Design, build, and deploy production AI applications for enterprise clients, spanning solution architecture, backend development, agentic workflows, cloud deployment, evaluation, and operationalization.
Diseñarás arquitecturas de IA agéntica y generativa basadas en LLM y RAG, liderarás soluciones en Azure AI y OpenAI, y definirás prácticas de gobernanza, seguridad y escalabilidad.
Diseñarás y liderarás soluciones de IA generativa basadas en LLM, RAG y agentes, definiendo arquitecturas, buenas prácticas y hojas de ruta para llevar casos de uso a producción.
Build and evaluate LLM-powered prototypes for gaming analytics, using multimodal game data and retrieval pipelines, then bring successful solutions into production with engineering teams.
Build and evaluate LLM-powered prototypes for gaming analytics, using multimodal game data and retrieval pipelines, then bring successful ideas into production with engineering teams.
