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# Gen AI Engineer

- **Company:** ApTask
- **Location:** Plano, TX, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Engineering, Computer Programming, Continuous Integration, Monitoring of Systems, Python (Programming Language), Machine Learning, Tensorflow, Management of Software Versions, Google Cloud, Enterprise Software Applications, Pytorch, Large Language Models, Multi-Agent Systems, Prompt Engineering, Deep Learning, Generative AI, Scikit Learn, Kubernetes, Machine Learning Operations, Data Pipelines, Docker, Microservices
- **Published:** September 10, 2026
- **Apply:** https://www.dice.com/job-detail/ac3a936b-a7b4-49b0-9c8f-7fe18a86ee75

## About the Role

· Job Summary We are seeking a highly skilled Senior AI Engineer to design, develop, and deploy AI-powered solutions that drive business value.

· The ideal candidate will have strong experience in Machine Learning, Deep Learning, Generative AI, Large Language Models (LLMs), MLOps, and cloud-based AI platforms.

· The role involves working closely with cross-functional teams to build scalable AI applications and bring innovative AI solutions into production., · Strong programming skills in Python.

· Hands-on experience with Machine Learning and Deep Learning frameworks such as TensorFlow, PyTorch, and Scikit-learn.

· Experience working with Generative AI, LLMs, RAG, AI Agents, and Prompt Engineering.

· Knowledge of Natural Language Processing (NLP) techniques and tools.

· Experience with vector databases such as Pinecone, Chroma, Weaviate, or FAISS.

· Familiarity with AI orchestration frameworks including LangChain and LlamaIndex.

· Strong understanding of MLOps tools and practices. Experience with cloud platforms such as Azure AI, AWS, or Google Cloud Platform.

· Knowledge of Docker, Kubernetes, and microservices architecture.

· Strong analytical, problem-solving, and communication skills.

## Description

· Design, develop, and deploy AI/ML solutions for enterprise applications.

· Build and optimize machine learning and deep learning models for production environments.

· Develop Generative AI applications using LLMs, Retrieval-Augmented Generation (RAG), and AI agents.

· Fine-tune and evaluate foundation models using domain-specific datasets. Implement prompt engineering strategies and AI orchestration frameworks such as LangChain or LlamaIndex. Develop scalable data pipelines for model training, evaluation, and deployment.

· Collaborate with product managers, architects, and business stakeholders to translate business requirements into AI solutions.

· Implement MLOps practices including CI/CD, model monitoring, versioning, and governance.

· Ensure AI models meet performance, security, scalability, and compliance requirements.

· Mentor junior engineers and contribute to AI best practices across the organization.


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