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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AWS Database Engineer / Cloud DBA - **Company:** OpenKyber LLC - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $156,000.0 - $166,400.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Computer Vision, Microsoft Azure, BigQuery, Cloud Computing, Cloud Engineering, Computer Programming, Databases, Continuous Integration, Data Governance, Monitoring of Systems, Python (Programming Language), Machine Learning, Natural Language Processing, Tensorflow, Azure Machine Learning, Search Technologies, Data Streaming, Systems Integration, Google Cloud, Cloud Platform System, Pytorch, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Deep Learning, Generative AI, Cloudformation, Event Driven Architecture, Build Management, AI Platforms, Scikit Learn, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Machine Learning Operations, Restful APIs, Terraform, Software Version Control, Docker, Microservices - **Published:** May 13, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=17903f6197e334a8 ## About the Role Do you have experience in Solution architecture design?, Do you have a Master's degree?, We are looking for a AI Architect for our client in T orrance, CA Job Title: AI Architect Job Location: T orrance, 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 a nd Education: Bachelor s degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or a related field. Master s degree preferred. 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