AI Engineer

About Sharebite

Sharebite is the leading meal benefits platform built exclusively for companies to feed their employees. Our platform allows employees to order meals from any restaurant while streamlining all of the ordering & billing requirements for the company. Every meal ordered through the Sharebite platform results in a meal donation to local partners like City Harvest and Feeding America to help combat food insecurity. To date, Sharebite has donated over 15 million meals.

About the Role

As an AI Engineer, you will play a key role in shaping how Sharebite applies AI across both its product and internal operations. You will begin by working closely with the product and engineering teams to build a deep understanding of the codebase, core workflows, business logic, and operational complexity behind the platform. We see that foundation as essential to building AI solutions that are not only innovative but genuinely useful.

As you grow into the role, you will identify high-impact opportunities to use AI to improve efficiency, streamline manual work, and enhance the product experience for customers and internal teams. You will be responsible for designing, building, and refining AI-powered tools, automations, workflows, and product features that are practical, scalable, and well-integrated into the business. This role is ideal for someone who wants to pair full stack engineering with applied AI work and have a meaningful influence on how the function develops over time.

A note on the role: this position starts as a Full-Stack Engineer and evolves into an AI Engineer over time. If you’re looking for a pure AI/ML research role, this likely is not the best fit. If you’re someone who loves building real products and wants to apply AI engineering over time, this role is perfect for you.

What You’ll Do

• Build and ship full-stack features across the product as you ramp up on the platform
• Develop a thorough understanding of our systems, data models, and business logic
• Identify high-leverage automation opportunities as you learn how the platform works
• Design and build AI agents and automated workflows using modern AI tooling
• Integrate LLMs into product workflows in ways that are reliable and production-safe
• Evaluate, iterate, and improve AI systems based on real-world performance
• Collaborate with product and engineering to solve user-facing problems
• Help define what effective, responsible AI engineering looks like at our company

Required Skills & Experience

• 5+ years of full-stack development experience, with a proven ability to own features end-to-end
• 1–2 years of hands-on AI engineering experience building and shipping LLM-powered systems in production
• Experience with at least one major AI orchestration framework such as LangChain, LangGraph, or AWS Bedrock
• Familiarity with LLM APIs (OpenAI, Anthropic, etc.), vector databases, RAG pipelines, and agent frameworks
• Strong software engineering fundamentals, including system design, testing, debugging, and clean code practices
• Clear communicator who can work across product and engineering teams

Who You Are

• Genuinely curious about how systems work, and not just how to layer AI on top of them
• Comfortable starting as a full-stack engineer and growing into AI engineering as you learn the product
• Thoughtful about where AI adds real value and where it doesn’t
• Someone who takes ownership and doesn’t wait to be told what to improve
• Excited by the idea of being the person who shapes how an entire company thinks about AI

What Success Looks Like

• 0–3 months: You’re shipping product features independently and have a strong mental model of how the platform works
• 3–6 months: You’ve shipped your first AI-powered workflow or agent into production
• 6–12 months: You’ve automated multiple high-impact workflows and are proactively identifying the next wave of opportunities