Clojure AI / LLM Engineer

Stylitics; New York (NY); On-site; USD 120,000 - 190,000; Full time

Job summary

Stylitics is seeking a versatile AI/LLM Data Engineer to shape the future of how Stylitics leverages large language models. You will fuse data science, software engineering, and prompt design to prototype, test, and deploy LLM workflows powering automation and content generation at scale.

You'll work with cross‑functional teams, contribute to production code in Clojure and Python, build dashboards, and develop internal tooling to reuse prompts, test cases, and model evaluations.

Qualifications

• Very strong SQL experience and data visualization skills.
• Experience contributing to production code.
• Experience with LLMs testing and prompt engineering.
• Proficiency in Python for experimentation and tooling.
• Solid understanding of system design and APIs.
• Ability to work cross‑functionally with product, design, and engineering.

Responsibilities

• Prompt engineering and testing with LLMs
• Context engineering to determine the right data
• Agentic workflow design
• Monitor and test LLM performance
• Contribute to production code (Clojure + Python)
• Analyze large data sets and build dashboards
• Develop internal tooling for prompt reuse, versioning, and test cases

Skills

Prompt engineering

Context engineering

LLM testing

Python programming

Clojure

SQL

Data visualization

Education

Computer Science degree

Data Science degree

Statistics degree

Tools

Google Cloud

GitLab

ClojureScript

Git

Cloud Functions

Job description

We are looking for a versatile and experienced AI / LLM Data Engineer to join our team and help shape the future of how Stylitics leverages large language models. In this role, you’ll combine your expertise in data science, software engineering, and prompt design to drive innovation in AI model based applications across our platform. You’ll work closely with cross-functional teams to prototype, test, and deploy LLM workflows that leverage internal and external models (primarily LLMs) to power intelligent automation and content generation at scale. This is a hands‑on role with high visibility and the opportunity to influence the way we build, monitor, and evaluate next‑generation AI systems. If you're excited about exploring the frontiers of generative AI and making a direct impact through production‑level contributions, we’d love to meet you.What you will do- Prompt engineering and testing with LLMs- Context engineering to determine the right data- Agentic workflow design- Help us build systems to easily monitor and test LLM performance- Contribute to production code (Clojure + Python)- Analyze large data sets- Build dashboards- Contribute as a thought leader to conversations around LLM usage- Develop internal tooling and software to support prompt reuse, versioning, and test case managementGreat to haves- Working experience with building test workflows for LLMs- Monitoring- Building/using test data sets for new model evaluation- Degree in Computer Science, Data Science, Statistics- Hands‑on experience in computer vision, image processing, and/or NLP

Responsibilities

• Prompt engineering and testing with LLMs
• Context engineering to determine the right data
• Agentic workflow design
• Help us build systems to easily monitor and test LLM performance
• Contribute to production code (Clojure + Python)
• Analyze large data sets
• Build dashboards
• Contribute as a thought leader to conversations around LLM usage
• Develop internal tooling and software to support prompt reuse, versioning, and test case management

Requirements

• Very strong SQL
• Experience contributing to production code
• Experience building data visualizations
• Experience with LLMs, testing, and prompt engineering
• Proficiency with Python for experimentation and tooling
• Solid understand of system design, use of APIs, and open source packages
• Demonstrated ability to evaluate model performance using structured test cases and metrics
• Comfortable collaborating cross‑functionally with product, design, and engineering teams
• Excellent communication skills, especially in explaining technical ideas to non‑technical audiences

Tech stack

• SQL
• Google Cloud
• Git & GitLab
• Clojure
• Python
• ClojureScript
• Machine Learning
• Cloud Functions