About the Company
Daisy is the forecasting platform food processors rely on for their most important supply and demand decisions. For too long, processors have run complex supply, production, and commercial planning on outdated spreadsheets and gut instinct, leaving millions in margin on the table. Behind Daisy is an engineering team that studies how each partner business actually operates and encodes that understanding into a platform built on advanced time series modeling and deep mathematical rigor, producing forecasts processors can trust. We have already significantly increased forecast accuracy for the processors we work with, helping them recover lost margins and run more resilient, profitable operations. Our mission is to build a more resilient and profitable future for food processing. We are well-capitalized, high-intensity, and we only hire the best.
About the Role
As a fullstack engineer at Daisy, you will work on the platforms, systems, and services that bring our predictive analytics to life at scale. You’ll collaborate across research and product teams to enable rapid iteration, high reliability, and secure delivery of novel features to food factories around the world. Your work will directly impact both the pace of product development and the stability of our production systems. This role leans infrastructure and some Python automation. You should genuinely enjoy that work, not just tolerate it.
Responsibilities
- Build and run our infrastructure and some Python automation: deployment pipelines, environments, and the tooling that lets the team move fast and safely.
- Build and maintain backend services that power the product, end to end.
- Help shape the data models and infrastructure that hold up as we scale from early clients to multi-tenant.
- Contribute to the frontend when it’s the fastest path to shipping.
Qualifications
Open to a range of experience levels; what matters most is the skills below and how fast you learn.
Required Skills
- Strong in Python; some Java or JavaScript/TypeScript preferred.
- Hands-on experience with a major cloud provider (GCP preferred; AWS, Azure, or OCI fine).
- Solid with relational databases.
- You actually like infrastructure and automation work: CI/CD, environments, infrastructure-as-code.
- Comfortable making pragmatic decisions with incomplete information; you favor a clean Phase 1 over a gold-plated one.
- Comfortable working in a high-pace environment.
- Adaptable and a fast learner; the stack and priorities will shift as we grow.
Preferred Skills
- Experience taking a service from prototype to production: observability, auth, infrastructure-as-code.
- Worked at an early-stage startup or as an early hire.
Key Skills
Ranked by relevance
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- Posted
- Jun 17, 2026
- Type
- Full-time
- Level
- Not Applicable
- Location
- Dublin
- Company
- Daisy
Industries
Categories
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