Staff Software Engineer, GTM & AI Strategy
About this role
Sales teams at Toast spend too much time navigating administrative friction, and this hire will solve that problem by building the foundational technology to automate account research, lead prioritization, and complex quoting logic. Operating as a hands-on technical lead on the GTM and AI Strategy Engineering team, the person selected will architect 0-to-1 internal tools that leverage large language models, agentic workflows, and retrieval-augmented generation pipelines. The team focuses on removing inefficiencies across the go-to-market stack rather than maintaining legacy infrastructure, making this an ideal fit for a pragmatic engineer who enjoys writing high-performance backend code and integrating complex data flows.
Success in the position requires deep backend experience combined with practical knowledge of deploying artificial intelligence models in production environments. Candidates should excel at designing event-driven architectures and connecting custom applications to enterprise data lakes and CRM platforms like Salesforce. Anyone who thrives on turning high-level product goals into resilient, observable, and scalable systems will find a strong cultural alignment with Toast's engineering philosophy.
What you will do
- Spend the majority of time writing code and architecting high-performance backend services and machine learning pipelines.
- Build and prototype 0-to-1 internal products from scratch that utilize large language models and agentic workflows for sales automation.
- Develop backend integrations connecting custom quoting engines, Salesforce, and internal data lakes for a low-latency user experience.
- Solve complex synchronization and architectural challenges across the go-to-market stack to ensure scalable and resilient systems.
- Translate high-level product goals into sequenced, production-ready code that delivers significant core capabilities with broad impact.
- Anticipate shifts in product needs by designing flexible, decoupled backend systems that evolve alongside company strategy.
- Ensure the operational reliability of go-to-market tools by implementing deep observability into every shipped service.
What you need
- Extensive background in backend programming languages such as Java, Go, or Python with a proven track record of building distributed systems.
- Practical, hands-on experience developing and deploying LLM agents within production environments.
- Strong ability to implement event-driven architectures and manage secure, high-integrity data flows across disparate systems.
- Hold a Bachelor's or Master's degree in Computer Science or a related technical field.
Nice to have
- Experience building internal sales tech or fintech tools that directly impact revenue.
- Familiarity with AWS data services including SageMaker, Lambda, and SQS.
- A strong motivation for eliminating human-in-the-loop friction through intelligent automation.
Benefits
- Competitive base salary with geographic pay zones
- Cash compensation including overtime, bonuses, or commissions if eligible
- Equity opportunities
- Comprehensive health and lifestyle benefits programs
Skills and tech stack
Questions candidates ask
What is the remote work policy for this position?
Toast embraces a hybrid work model that fosters in-person collaboration while valuing individual needs. Candidates can review regional in-office expectations by visiting the locations page on the company career site.
How is the salary determined for this role?
The base salary range spans from $151,000 to $309,000 USD depending on the designated geographic pay zone. Starting compensation is determined based on individual skills, experience, and geographic location.
What tools and technologies will I be working with?
The tech stack involves backend languages like Java, Go, and Python alongside LLM agents, RAG pipelines, event-driven architectures, Salesforce, and AWS data services.
What does the hiring process look like?
The company uses AI tools exclusively to support recruiters and interviewers with tasks like note-taking and summarization. All hiring decisions are made by people, and candidates are asked to complete interviews and assessments without real-time AI tools or recording bots.