AI / LLM Engineer

About the role

The role is focused on developing and implementing advanced AI and Large Language Model (LLM) technologies within a production environment. The position requires a deep understanding of machine learning and software engineering principles, with a particular emphasis on applying these concepts to real-world problems.

Responsibilities

• Build and optimize retrieval and recommendation systems using LLMs and other applied ML techniques.
• Design and implement data ingestion and ETL pipelines to handle large, complex datasets.
• Develop and integrate third-party APIs into backend services, ensuring secure and efficient data flow.
• Evaluate and iterate on model and retrieval outputs to ensure optimal performance.
• Collaborate with cross-functional teams to develop and deploy scalable, secure, and efficient AI solutions.

Requirements

• Minimum 3-5 years of software engineering experience, with at least 1-2 years in building with LLMs or applied ML in a production or near-production setting.
• Strong proficiency in Python (or comparable) and solid engineering fundamentals such as testing, version control, and clean code practices.
• Hands-on experience with RAG systems, embeddings, vector databases, and chunking/indexing strategies.
• Experience with data ingestion/ETL pipelines and working with large, messy datasets.
• Experience integrating third-party APIs into backend services, including authentication flows and webhook/event-driven patterns.
• Hands-on experience with LLM APIs and at least one orchestration framework.
• Experience evaluating model and retrieval outputs and building evaluation sets.
• A careful approach to data access, permissions, and handling sensitive information.
• Familiarity with at least one major cloud platform (AWS preferred).

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field or equivalent practical experience.

Skills

• Python programming
• Software engineering fundamentals
• RAG systems development
• Data ingestion and ETL pipelines
• API integration
• Model evaluation and iteration
• Data security and privacy
• Cloud platform familiarity (AWS)

Benefits

• Competitive compensation package
• Flexible work schedule
• Professional development opportunities
• Health and wellness programs

Pay

Competitive salary commensurate with experience.

Schedule

Full-time, Monday through Friday.