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# AI Engineer

- **Company:** Epistemix, Inc.
- **Location:** Pittsburgh, PA, United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Data Validation, Serialization, Database Models, Python (Programming Language), Machine Learning, Performance Tuning, SQLAlchemy, Systems Architecture, AI Infrastructure, Large Language Models, Fastapi, Information Technology, Machine Learning Operations, Virtual Agents, Restful APIs, Docker
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/ai-engineer-epistemix-8130088

## About the Role

* Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field (or equivalent experience).
 * 3+ years of experience developing AI/ML applications in production environments.
 * Proven track record of working with LLMs, NLP models, or AI-driven systems.
 * Experience designing and optimizing high-performance, scalable APIs.
 * Strong problem-solving skills and ability to work in a fast-paced environment.
 * Must be legally authorized to work in the United States and not require employer sponsorship now or in the future., * Python - Advanced proficiency in writing clean, efficient, and scalable code.
 * Pydantic - Strong experience in data validation, serialization, and structured model definition.
 * LLM Evaluation - Ability to assess model performance, optimize outputs, and fine-tune AI behavior.
 * Prompt Optimization - Expertise in crafting, refining, and iterating prompts for optimal AI performance.
 * SQLAlchemy - Hands-on experience with database modeling, ORM techniques, and performance tuning.
 * FastAPI - Proven ability to develop and maintain APIs with FastAPI for AI-driven applications.

Nice to Have Experience

 * Experience with vector databases (e.g., Pinecone, Weaviate, FAISS) for efficient AI retrieval.
 * Familiarity with Docker & Kubernetes for containerized AI application deployment.
 * Knowledge of cloud platforms (AWS, GCP, or Azure) for scaling AI infrastructure.
 * Understanding of retrieval-augmented generation (RAG) techniques.
 * Background in MLOps practices for automating AI model deployment and monitoring.

## Description

* Craft clean, testable, and maintainable code to enable AI-generated agent-based models.
 * Own the software from requirements development through deployment and maintenance that enable decision makers to generate agent-based models that address critical business questions and data scientists to build agent-based models more quickly that answer the questions of decision makers.
 * Design, build, test, and deploy a scalable system architecture so that AI-generated models can be validated by data scientists and deliver results back to decision makers quickly.
 * Own the engineering solution and collaborate with internal teams to ensure alignment with company strategy.


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