Staff Software Engineer, Applied AI
Toast · Bengaluru
| Company | Toast |
|---|---|
| Role | Staff Software Engineer, Applied AI |
| Location | Bengaluru |
| Work mode | Hybrid |
| Experience | 6+ years |
| Job type | Full-time |
About this job
Toast is hiring a Staff Software Engineer in Bengaluru for its New Ventures team, which is building a new AI-powered product. You will take ideas from early prototypes to features that restaurant customers rely on, working closely with Product and Design.
The role covers LLM-powered workflows and agents, evaluations for AI quality, and the backend services and APIs behind the product. It suits someone who likes ambiguous problems and still wants to stay close to the code. The role follows Toast's hybrid model.
Eligibility
- 8 to 12 years of backend, API and production software experience
- Deep Java or Kotlin skills, with strong testing and design practice
- Experience building and scaling cloud-native distributed systems on AWS
- Hands-on experience shipping LLM-powered apps, including tool-using agents
- Experience designing evaluations for AI systems and using results to improve them
Skills required
What you will do
- Own core capabilities of a new AI product from first approach to launch
- Build prototypes to test assumptions, then decide what to evolve or rebuild
- Build LLM workflows and agents and define what good AI performance means
- Shape backend services, APIs and data models so the product can grow
- Mentor engineers and set good practice for AI coding assistants
How to apply
- Open the official Toast job page with the Apply button and submit your application there.
- Tailor your resume to LLM or agent features you shipped, how you measured their quality, and the backend systems behind them.
Before the interview, prepare:
- Agent design: when to use model reasoning, tools or plain code for a multi-step task
- AI evaluations: build an eval set from real customer tasks and track regressions
- Backend design on AWS: APIs, data models and scaling a new product as usage grows
- Ambiguity story: a project with unclear requirements and how you drove it to a result
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