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# AI Engineer

- **Company:** QUALITEST
- **Location:** Austin, TX, United States (Remote available)
- **Experience:** Experienced
- **Salary:** $110,000.0 - $115,000.0
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Continuous Integration, Information Engineering, Monitoring of Systems, Python (Programming Language), Machine Learning, OpenAI, Tensorflow, Requirements Management, Management of Software Versions, Pinecone, Pytorch, LangChain, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Model Validation, Generative AI, Agentic-AI, Containerization, Kubernetes, HuggingFace, CrewAI, Weaviate, AutoGen, Machine Learning Operations, FAISS, Claude, Virtual Agents, Docker
- **Published:** October 31, 2026
- **Apply:** https://www.careerbuilder.com/job-details/ai-engineer-austin-tx--031718b2-26c8-43f5-8169-e3658fae4c78

## About the Role

Artificial Intelligence (AI), Quality Engineering, Artificial Intelligence (AI), Machine Learning, Use Cases, Business Case, Artificial Intelligence (AI) Agents, Cross-Functional, Requirements Management, Product Engineering, * 3+ years of experience with AI/ML engineering or related roles

 * Strong hands-on experience with Generative AI (GenAI) - LLMs, prompt engineering, fine-tuning
 * Practical knowledge of AI agents and agentic frameworks (e.g., LangChain, LangGraph, AutoGen, CrewAI, or similar)
 * Proficiency in Python and common ML/AI libraries (PyTorch, TensorFlow, Hugging Face, etc.)
 * Experience with LLM APIs (OpenAI, Anthropic Claude, Azure OpenAI, etc.)
 * Experience building RAG pipelines and working with vector databases (Pinecone, FAISS, Weaviate, etc.)Solid understanding of NLP concepts and model evaluation techniques
 * Experience with cloud platforms (AWS, Azure, or GCP) for AI/ML deploymentFamiliarity with MLOps practices - CI/CD for ML, model monitoring, versioning
 * Strong problem-solving skills and ability to work in a fast-paced, evolving environment
 * Excellent communication skills to collaborate with technical and non-technical stakeholders

Good to Have

 * Experience with multi-agent orchestration and tool-calling frameworks
 * Knowledge of AI governance, responsible AI, and model risk management
 * Experience with containerization (Docker, Kubernetes)
 * Exposure to domain-specific AI applications (e.g., healthcare, finance, insurance)

## Description

We are looking for an experienced AI Engineer to design, build, and deploy AI-powered solutions, with a strong focus on Generative AI (GenAI) applications and AI agent frameworks. The ideal candidate will have hands-on experience building production-grade AI systems and a solid understanding of modern LLM-based architectures., 1. Design, develop, and deploy machine learning and generative AI models/solutions for business use cases

 2. Build and orchestrate AI agents capable of autonomous task execution, tool use, and multi-step reasoning

 3. Fine-tune and optimize large language models (LLMs) for specific domains and applications

 4. Develop and integrate Retrieval-Augmented Generation (RAG) pipelines

 5. Collaborate with cross-functional teams (product, data engineering, architecture) to translate business requirements into AI solutions

 6. Implement prompt engineering best practices and evaluate model outputs for accuracy, safety, and performance

 7. Build scalable APIs/services to deploy AI models into productionMonitor, evaluate, and continuously improve AI model performance (accuracy, latency, cost)

 8. Ensure responsible AI practices - bias mitigation, guardrails, and data privacy compliance