Data Engineer (AI)

inKind•Austin, TX

6d•$135,000 - $155,000•Onsite

About The Position

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.

Requirements

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)

Responsibilities

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 but not limited to: leadership, the development team, the finance team, and the data science team, in order 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

Benefits

100% employer-paid medical coverage through Blue Cross Blue Shield for employees on our base healthcare plan
100% employer-paid Dental PPO coverage for employees
Vision coverage available
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