Quick Overview
Seniority
Mid Senior
Work mode
Hybrid
Location
Plano, TX, United States
Posted
1 week ago
DockerMicroservicesAWSMLOpsMachine LearningNLPScikit-learnAzureDeep LearningGenerative AIGoogle CloudKubernetesLLMPyTorchPythonTensorFlow
Job Description
Must-have skills :
- AI-enabled Application Development, Generative AI Fundamentals (Strong), LLM Application Frameworks (Strong), Python (Strong)
Job Description:
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.
Key Responsibilities:
- 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.
Required Skills:
- 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.
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