AI Architect

Position-AI Architect
Location-Torrance, CA

Job Description
 Experience

• 10+ years overall experience, with 5+ years in AI/ML and GenAI architecture and implementation, and strong cloudnative delivery experience

Key Responsibilities
AI Architecture & Solution Design

• Design endtoend AI / ML / GenAI architectures for Automotive and Manufacturing use cases
• Define cloudnative reference architectures for AI workloads on AWS, Azure, or Google Cloud Platform
• Translate business requirements into secure, scalable, and costoptimized AI solutions
• Align AI architectures with enterprise security, compliance, and governance standards

AI / ML / GenAI Implementation

• Lead handson implementation of AI solutions, including:
  • Machine Learning and Deep Learning models
  • GenAI solutions using LLMs (RAG, embeddings, prompt engineering)
  • Computer Vision and NLP use cases relevant to manufacturing and automotive
• Ensure transition from POC → Pilot → Production
• Build and deploy AI pipelines for training, inference, and monitoring

Automotive & Manufacturing Use Cases

• Design and deliver AI solutions for:
  • Predictive maintenance and asset health monitoring
  • Quality inspection using computer vision
  • Smart manufacturing / Industry 4.0 initiatives
  • Supply chain optimization and demand forecasting
  • Connected vehicle and telematics analytics
  • Warranty analytics and rootcause analysis
• Work with plant, operations, and engineering teams to align AI solutions with realworld workflows

Cloud & Platform Engineering

• Architect AI platforms on:
  • AWS (SageMaker, Bedrock, EKS, Lambda, S3)
  • Azure (Azure ML, Azure OpenAI, Synapse, Data Factory)
  • Google Cloud Platform (Vertex AI, BigQuery, Cloud Run)
• Design containerized and microservicesbased AI systems
• Implement integrations with enterprise systems (ERP, MES, PLM, IoT platforms)

MLOps, Governance & Scalability

Required Skills & Experience

AI / Data Technologies

• Strong expertise in:
  • Machine Learning, Deep Learning, NLP
  • GenAI and LLM architectures (RAG, vector search)
• Handson experience with:
  • TensorFlow, PyTorch, Scikitlearn
  • LangChain / LlamaIndex (preferred)
  • Vector databases (Pinecone, FAISS, Milvus)

Cloud & Engineering

• Strong experience in at least one major cloud platform
• Solid programming skills in Python (mandatory)
• Experience with:
  • REST APIs, eventdriven architectures
  • Docker, Kubernetes
  • Infrastructure as Code (Terraform / ARM / CloudFormation)

Domain Experience (Mandatory)

• Proven experience delivering AI solutions for:
  • Automotive
  • Manufacturing / Industrial enterprises
• Strong understanding of plant operations, engineering data, and operational KPIs