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SeniorFull-timePythonRustRailsAWSData ScienceCI/CDAIML
Salary Range
$26,520 - $35,880 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for an AI Engineer focused on Agentic Workflows to join our team at Toast. This role involves designing and building intelligent, autonomous systems that orchestrate reasoning, actions, and tools to solve complex business problems. You will work at the intersection of LLMs, systems engineering, and product innovation, partnering with various teams to bring agent-based capabilities into production.
Key Responsibilities
- →Design and build agentic AI workflows using LLMs to autonomously reason, plan, and act across complex tasks
- →Architect multi-agent and tool-using systems that integrate with internal services, APIs, and data platforms
- →Collaborate closely with Product, Data Science, ML Engineering, and Platform teams to translate business problems into agent-driven solutions
- →Break down large AI initiatives into iterative, shippable components that deliver incremental value
- →Productionize agent workflows with strong observability, reliability, and performance guarantees
- →Implement evaluation, monitoring, and guardrails for agent behavior, correctness, latency, and cost
- →Incorporate human-in-the-loop patterns where appropriate to ensure safety, trust, and usability
- →Document architectures, decisions, and best practices to enable team-wide adoption and scalability
- →Stay current with advancements in LLMs, agent frameworks, prompting strategies, and AI safety
- →Contribute to building a strong AI engineering culture within the Data & AI organization
Requirements
- ✓Bachelor’s or Master’s degree in Computer Science, AI, ML, or related technical field
- ✓5+ years of experience in full stack Data Scientist, ML engineering, or applied AI roles
- ✓Hands-on experience with LLMs and agentic systems (e.g., LangChain, LangGraph, AutoGen, custom frameworks)
- ✓Strong proficiency in Python and experience building production-grade systems
- ✓Experience integrating LLMs with tools, APIs, databases, and workflows
- ✓Experience deploying LLM-based systems at scale
- ✓Solid understanding of software engineering best practices: OOP, testing, CI/CD, version control
- ✓Experience in building and productionizing embedding models, Data classical ML and deep learning models.
- ✓Familiarity with cloud-native systems and AWS services (ECS, EKS, Lambda, DynamoDB, S3, SageMaker, etc.)
- ✓Ability to reason about trade-offs in latency, cost, reliability, and correctness
- ✓Strong collaboration and communication skills across technical and non-technical stakeholders
Benefits
- ★Hybrid work model that fosters in-person collaboration while valuing individual needs
- ★Commitment to creating an accessible and inclusive hiring process
- ★Strong AI engineering culture within the Data & AI organization
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