AI Architect

Job Title: AI Architect

Job Location: Torrance, CA

Job Type: Contract

Job Overview:

Pay Range: $75hr - $80hr

Requirement/Must Have:

• 10+ years of overall IT experience.
• 5+ years of experience in AI/ML and Generative AI architecture and implementation.
• Strong experience with cloud-native AI solution delivery.
• Hands-on expertise in Machine Learning, Deep Learning, NLP, and Generative AI technologies.
• Strong programming experience with Python.
• Experience with TensorFlow, PyTorch, and Scikit-learn.
• Experience designing and implementing GenAI and LLM-based architectures including RAG, vector search, embeddings, and prompt engineering.
• Strong experience with at least one major cloud platform such as AWS, Azure, or Google Cloud Platform.
• Experience with Docker, Kubernetes, REST APIs, and event-driven architectures.
• Experience implementing MLOps frameworks and AI governance processes.
• Proven experience delivering AI solutions within Automotive and Manufacturing industries.
• Strong understanding of plant operations, engineering data, and operational KPIs.

Experience:

• Experience designing end-to-end AI, ML, and GenAI architectures.
• Experience implementing scalable AI platforms and cloud-native AI workloads.
• Experience transitioning AI solutions from proof of concept to production.
• Experience building AI pipelines for model training, deployment, inference, and monitoring.
• Experience integrating AI systems with ERP, MES, PLM, and IoT platforms.
• Experience with predictive maintenance, quality inspection, smart manufacturing, and connected vehicle analytics.
• Experience implementing monitoring for model drift, data quality, and operational performance.
• Experience with Infrastructure as Code tools such as Terraform, ARM, or CloudFormation.
• Experience working within enterprise-scale and multi-vendor environments.

Responsibilities:

• Design end-to-end AI, ML, and Generative AI architectures for Automotive and Manufacturing use cases.
• Define secure, scalable, and cost-optimized cloud-native AI reference architectures.
• Lead implementation of machine learning, deep learning, NLP, and GenAI solutions.
• Build and deploy AI pipelines for training, inference, retraining, and monitoring.
• Design AI solutions for predictive maintenance, quality analytics, supply chain optimization, and connected vehicle use cases.
• Develop AI-powered computer vision and NLP solutions for manufacturing operations.
• Collaborate with plant, engineering, and operations teams to align AI solutions with business workflows.
• Architect AI platforms using AWS, Azure, or Google Cloud Platform services.
• Implement containerized and microservices-based AI systems.
• Establish MLOps frameworks for CI/CD, model versioning, deployment, and governance.
• Monitor model performance, pipeline health, data quality, and operational efficiency.
• Ensure compliance with responsible AI, explainability, security, and governance standards.
• Provide technical leadership and guidance across AI delivery initiatives.

Should Have:

• Experience with LangChain or LlamaIndex.
• Experience with vector databases such as Pinecone, FAISS, or Milvus.
• Exposure to IoT platforms and streaming data architectures.
• Experience in operational analytics or AMS/support platforms.
• Cloud and AI certifications from AWS, Azure, or Google Cloud Platform.
• Experience working in global enterprise transformation programs.

Skills:

• Artificial Intelligence.
• Machine Learning.
• Deep Learning.
• Natural Language Processing.
• Generative AI.
• Large Language Models.
• Retrieval-Augmented Generation.
• Prompt Engineering.
• Vector Search.
• TensorFlow.
• PyTorch.
• Scikit-learn.
• LangChain.
• LlamaIndex.
• Pinecone.
• FAISS.
• Milvus.
• Python.
• AWS SageMaker.
• AWS Bedrock.
• Azure ML.
• Azure OpenAI.
• Vertex AI.
• BigQuery.
• Docker.
• Kubernetes.
• REST APIs.
• Event-Driven Architecture.
• Terraform.
• ARM Templates.
• CloudFormation.
• MLOps.
• CI/CD.
• Model Monitoring.
• Data Governance.
• Computer Vision.
• Cloud-Native Architecture.

Qualification and Education:

• Bachelor s degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or a related field.
• Master s degree preferred.
• Relevant cloud and AI certifications are a plus.