AI Architect

Posted 1 day ago

San DiegoLast seen today

Summary

Design and deliver enterprise-scale AI/ML solutions leveraging cloud technologies, with hands-on expertise in LLMs, agentic frameworks, and AI orchestration. This role requires 5–7 years of cloud experience and 2–3 years of practical AI/ML work, including proficiency in AWS AI services (Bedrock, SageMaker), prompt engineering, RAG pipelines, and responsible AI principles. You will architect AI-driven applications, optimize AI cost and performance, manage MLOps workflows, and integrate AI systems with enterprise data platforms and microservices architectures. Strong communication skills are essential to present technical concepts to both technical and executive audiences.

Data Science DevOps / Infrastructure AI AWS Python Agent To Agent Communication Agentic Frameworks Amazon Bedrock Amazon Bedrock Guardrails Amazon Q Apm Athena Audio Processing Aurora AWS Cdk AWS Strands Agents AWS X Ray Bias Detection Chunking Strategies CI CD Cloudformation Cloudwatch Container Orchestration Content Filtering Data Lakes Data Pipeline Devsecops Document Understanding Drift Detection Dynamodb Ecs Eks Embedding Models Enterprise Integration Patterns Event Driven Architecture Experiment Tracking Feaf Finops Frontier Model Evaluation Glue Image Analysis Infrastructure As Code Kendra LangChain Langgraph Linux Litellm LLM Fine Tuning LLM Function Calling LLM Large Language Models Machine Learning Microservices Mlflow Mlops Model Benchmarking Model Context Protocol Model Quantization Model Risk Management Model Versioning Monitoring Multimodal AI Networking Observability Open Webui Pii Handling PostgreSQL Prompt Caching Prompt Engineering RAG Retrieval Augmented Generation Redshift Responsible AI Restful API S3 Sagemaker Sagemaker Pipelines Scripting Security Serverless Architectures Snowflake Storage Structured Output System Administration Terraform Togaf Token Management Vector Stores Windows Zachman Framework