AI- Data Engineer: Build Scalable Data & LLM Apps

Data Engineering is a key role in the development team and is responsible for building and maintaining the AI-ready data foundation that powers inKind’s intelligent products, machine learning models, and large language model (LLM) applications. The position requires working across departments to build, operate, and optimize highly available data pipelines that feed analytics, ML training and inference, and retrieval-augmented generation (RAG) systems.

• Responsible for the design, deployment, and maintenance of the business’s data and AI platforms
• Own architectural processes and decisions for various data models within the organization, including schemas, vector stores, and knowledge bases that support AI and LLM use cases
• Design and operate feature pipelines, embedding pipelines, and evaluation datasets that support machine learning model training, fine‑tuning, and continuous evaluation
• Work cross-functionally with various departments—including leadership, the development team, the finance team, and the data science team—to convert data into understandable information and AI‑ready inputs for other professionals
• Ensure implemented data and AI systems have relevant security, privacy, and data‑governance controls—particularly around data flowing into and out of third‑party LLM providers

• Bachelor’s degree in Computer Science, Applied Mathematics, Engineering, or any other technology related field. An equivalent of this educational requirement in working experience is also acceptable
• 5+ years professional database development experience, preferably as a Data Engineer in a fast‑paced environment and complex business setting
• Expert level knowledge of SQL with focus on writing and optimizing queries
• Demonstrated experience building and maintaining reliable and scalable ETL/ELT using Snowflake, dbt, and AWS architecture
• Proficiency in Python and modern AI/ML tooling and experience integrating with LLM APIs (Anthropic, OpenAI, etc.)
• Expert problem solving ability and maker’s mentality; vast experience designing & architecting new features and solutions from scratch—especially those that blend traditional data systems with AI‑powered components
• Eagerness to discover innovative ways to work faster and more efficiently, including leveraging AI coding assistants and agents, while balancing competing concerns (tech debt, cost, security, complexity, etc.)
• Proactive communication, both written and spoken, and excellent ability to work well with others, in‑person and remotely
• Courage when it comes to raising concerns and asking questions
• Ability to stay up‑to‑date with new frameworks and tools—especially in the rapidly evolving AI/ML space—to speed up development, while keeping a sharp eye out for potential vulnerabilities and edge cases (including prompt injection and data leakage to third‑party AI services)

At inKind, we believe supporting our employees goes beyond compensation. We’re committed to creating an environment where our team can thrive both professionally and personally.

• 100% employer‑paid medical coverage through Blue Cross Blue Shield for employees on our base healthcare plan
• Company‑paid Short‑Term Disability coverage

• Unlimited Paid Time Off
• 9 paid company holidays annually
• Generous parental leave and child care benefits

• Career development and training opportunities designed to support long‑term professional growth
• Daily catered lunches and office snacks
• Credits to dine within the inKind restaurant network
• Collaborative, in‑person culture based in Austin, Texas
• Dog‑friendly office environment with views of downtown Austin

$135,000 - $155,000, DOE

Who we are:

inKind connects passionate diners with exceptional restaurants across the country. inKind partners with thousands of restaurants and has millions of users who want to discover great places, dine confidently, and earn meaningful rewards. Through the inKind app, guests earn 20% back every time they dine, turning everyday meals into something more rewarding. From celebrated restaurant groups like José Andres and Michael Mina to beloved neighborhood favorites,…