Staff Software Engineer - Intelligence Platform
Toast is hiring a Staff Software Engineer - Intelligence Platform in Dublin, Ireland. Level rates it ; you can apply on Toast.
Level's read on this job
- Level rates this software engineer role Works on AI ●●●○: the daily work is on AI products, without building the model.
- The posting mentions Databricks, Kotlin and Java among its tools and skills.
- Level classes it as a senior role.
- Toast has 320 other open roles on Level.
- Posted within the past week.
AI in this role
Lead technical architecture and development for Toast's Intelligence Platform serving data and AI agents.
Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.
We are hiring a Staff Software Engineer to join Toast Reporting Experience (TREX) in Dublin. TREX is building the Intelligence Platform: a governed data layer that brings Toast's restaurant intelligence to prospects, operators, Toast IQ and AI agents.
As a Staff Software Engineer, you will be the technical lead for the Intelligence Platform. You will establish its architecture on Toast's data lake and make the key design calls across data processing, privacy, publishing and serving. You will work closely with Data Platform, Marketing, Product, Legal and Data Science, do deep hands-on work, and grow the engineers on your team. You will take the platform from its first version, a regular publication of aggregated benchmark data, to fresher data, self-serve access for Marketing, and eventually real-time access for AI agents. Success looks like new data products shipping on the platform quickly and safely.
A day in the life (Responsibilities)
- Own the technical vision and end-to-end architecture of the Intelligence Platform, from early design through production rollout
- Work hands-on with Kotlin/Java, Spark and Iceberg on Toast's data lake, writing the code that sets the pattern for others
- Move fast from idea to proof of concept: ship early versions, get feedback from Marketing and other partners, and iterate
- Build privacy and compliance into the platform from the start: work with Legal, Investor Relations, Privacy and Data Science to define the data-access rules and minimum group sizes, and enforce them in code so every published number is aggregated, anonymized and auditable
- Create reusable building blocks so every data product on the platform meets the same bar for quality and safety
- Design the flows that let tools and AI agents access the data efficiently, safely and at scale
- Partner with Marketing, Product, Legal, Investor Relations and Data Science to turn business goals into a technical roadmap
- Set the bar for reliability and quality, and mentor other engineers through design reviews, code reviews and the example you set
- Use AI tooling as a genuine force multiplier in your day-to-day work and help the team do the same
What you'll need to thrive (Requirements)
- 5+ years in software engineering, building data-intensive or distributed systems, including technical leadership of projects involving multiple teams
- Demonstrated ability to understand complex data domains at scale, and to turn them into reliable data products
- Proficiency in Java, Kotlin or another object-oriented language
- Experience with cloud-native data platforms on AWS
- Strong SQL and data modeling skills on large datasets
- Experience building data products or platforms that other teams depend on
- Experience handling sensitive data responsibly, such as aggregation, anonymization or access controls
- Ability to explain technical trade-offs clearly to non-engineering partners
- Experience with Apache Spark, Apache Iceberg, Snowflake or Databricks is a bonus
**This is a hybrid role requiring two days per week in our Dublin office.**
Our tech stack
The Intelligence Platform will source data from multiple sources: OpenSearch, Data Lake, Snowflake.
Toast's data lake is built on AWS: Apache Iceberg tables on S3 and Apache Spark for data processing. TREX's backend services are primarily Kotlin and Java, use Apache Pulsar for messaging, and serve data to other teams through APIs, including federated GraphQL.
AI at Toast
At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.
Our Total Rewards Philosophy
We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at https://careers.toasttab.com/toast-benefits.
How Toast Uses AI in its Hiring Process
Throughout the hiring process, our goal is to get to know you. We use AI tools to support our recruiters and interviewers with tasks like note-taking, summarization, and documentation of interviews to ensure they can be fully focused on your conversation. All hiring decisions are made by people. We ask that you complete interviews and assessments on your own, without real-time AI tools, recording, or transcription bots, unless we tell you otherwise in advance. To learn more: https://careers.toasttab.com/ai-in-hiring
Our Approach to Hybrid Working
We embrace a hybrid work model that fosters in-person collaboration while valuing individual needs. Our goal is to build a strong culture of connection as we work together to empower the hospitality community, regardless of location. Please visit the Locations page on our career site to learn more about our in-office expectations by region: https://careers.toasttab.com/locations-toast
People Are the Secret Ingredient in Our Recipe for Success
At Toast, our employees are our secret ingredient—when they thrive, we thrive. The restaurant industry brings together people with a wide range of backgrounds, experiences, and perspectives, and we value that same breadth at Toast. We strive to build a culture grounded in authenticity, respect, and humility, where every Toaster has a real opportunity to grow, contribute, and do their best work—raising the bar in delivering exceptional experiences for our customers and each other.
Apply today!
Toast is committed to creating an accessible and inclusive hiring process. As part of this commitment, we strive to provide reasonable accommodations for persons with disabilities to enable them to access the hiring process. If you need an accommodation to access the job application or interview process, please contact candidateaccommodations@toasttab.com.
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How we rate this
Staff Software Engineer - Intelligence Platform at Toast rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- Typical software engineer job
- $168k
This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a project where distributed systems was part of your work. What did you do?
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where technical leadership was part of your work. What did you do?
- Walk me through how you've used Databricks in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: AI agents, Distributed Systems, Data Engineering, Technical Leadership, and Databricks. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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