Tebi - AI Engineer
Requirements
• You’ll work closely with product and engineering to put intelligence into the hands of hospitality teams. That could be an agent that answers questions about a restaurant’s finances in real time, one that automates repetitive back-office tasks, or internal tools that help us move faster. • 7+ years in software engineering, with a solid base in data or ML engineering • Hands-on experience building and shipping LLM agents to production, not just prototypes. You’ve dealt with flaky tool calls, runaway loops, hallucinated arguments and token budgets, and you have opinions on how to handle them. • Strong data modeling and data warehousing fundamentals, plus experience with ingestion, transformation and data quality • Strong SQL, and experience with pipeline tools (e.g. Airflow, dbt) and analytical or cloud data platforms (e.g. ClickHouse, BigQuery, Snowflake) • Experience evaluating and monitoring LLM systems, and an understanding of the full lifecycle from experiment to deployment to ongoing improvement • Backend engineering skills: you’re comfortable building the API endpoint that exposes an agent’s output to the frontend, or the service an agent calls as a tool • Clear communication, including the ability to explain trade-offs in latency, cost, accuracy and complexity to product partners • A product mindset. You care about how your work lands with users, and you’re keen to meet customers face to face to understand their needs. • This probably isn't the role for you if you have been working with AI agents to improve your day to day working flows but you haven’t built an Agent in the production. • People who succeed at Tebi are independent, curious and passionate about hospitality. If this speaks to you we can be the right fit. Learn more about how we work from our Recipe here: https://www.tebi.com/gb/careers .
Responsibilities
• Design, build and operate production agents: orchestration, tool and function calling, memory, multi-step reasoning, and integration with Tebi’s backend services • Build the data foundations agents rely on, including real-time and batch pipelines over financial and operational data, retrieval layers, and well-modeled datasets agents can query safely and accurately • Turn APIs and internal services into well-defined agent tools, and own the contracts between agents and the rest of the platform • Set up evaluation for agent behavior: offline eval sets, LLM-as-judge and human review, regression testing on prompt and model changes, and feedback loops that improve agents over time • Own observability for agents in production by tracing sessions, tool calls and model calls, and tracking latency, cost, error rates and quality • Work with product teams to find where agents can meaningfully improve the customer experience or internal workflows, and say clearly where they can’t • Make sure agents handle data securely and responsibly, with sensible guardrails, access controls, and protection against prompt injection and data leakage
Benefits
• Start-up Equity • Lunch Provided in Office • Team building events • Unlimited time off • What is Restaurant Software? • Restaurants and other merchants use various software systems such as Point of Sale (POS), Reservations, Kitchen Display Systems (KDS), Payments, Inventory, Staffing, and the list goes on. These systems all need to speak to each other which they frequently don’t. It’s a mess, and we are fixing it. • From buying a croissant at a cafe to having dinner with friends, it’s a €4 Trillion+ global market and a critical part of everyday life in today's economy. • How we use AI at Tebi • We use AI the way our merchants use Tebi, to cut out the friction and get to what matters faster. We believe in a world where AI increases quality, efficiency and speed. • At Tebi, AI isn't a policy or a checkbox, it's just part of how we work. It helps us write, analyse, build, and improve but doesn’t make the last call. If there's a smarter way to do something, we want to find it.
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