AI Consultant / Architect

Hi,

Our client is looking for an AI Consultant / Architect in Austin, TX  location below is the detailed requirement.

Job Title: AI Consultant / Architect  
Location: Austin, TX  

Job Description:

• Bachelor’s degree in related field.
• 10+ years in software engineering or data science; 5+ years in AI/ML architecture roles
• Deep expertise in machine learning, deep learning, and statistical modeling
• Hands-on experience with LLMs (GPT, Claude, LLaMA, Mistral) and generative AI application development
• Strong proficiency in Python; experience with TensorFlow, PyTorch, Scikit-learn, and Hugging Face
• Solid understanding of Transformer architecture, attention mechanisms, and NLP fundamentals
• Experience designing RAG pipelines with vector databases (Pinecone, ChromaDB, Weaviate, FAISS)
• Proficiency with cloud AI services on AWS (SageMaker, Bedrock), Azure (OpenAI, ML Studio), or Google Cloud Platform (Vertex AI)
• Strong knowledge of MLOps practices MLflow, Kubeflow, model monitoring, feature stores
• Familiarity with agentic AI frameworks LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel
• Experience with containerization and orchestration: Docker, Kubernetes
• Understanding of data engineering principles ETL, data lakes, streaming pipelines (Kafka, Spark).
• Define and own the enterprise AI/ML architecture strategy, including model development pipelines, MLOps platforms, and LLM integration patterns
• Design scalable, secure, and maintainable AI systems leveraging cloud-native services (AWS, Azure, Google Cloud Platform)
• Architect Retrieval-Augmented Generation (RAG) systems, vector database solutions, and knowledge graph integrations
• Architect fine-tuning pipelines (LoRA, QLoRA, PEFT) for domain-specific model adaptation
• Define prompt engineering standards, guardrails, and output validation frameworks
• Design end-to-end MLOps pipelines covering data ingestion, model training, evaluation, deployment, monitoring, and retraining
• Establish CI/CD practices for ML models and AI applications
• Drive adoption of Model Context Protocol (MCP) and emerging agentic standards