Principal AI Engineering Architect
Core
Lead the design and delivery of complex, multi-domain systems spanning cloud, data, and AI, with deep mastery of multi-agent agentic AI solutions.
Role type
Principal AI Engineering Architect (hands-on IC with strategy & mentorship)
Builds
Production-grade multi-agent agentic AI systems, cloud-native solutions, and scalable ML platforms
Domain
Enterprise AI, Cloud Infrastructure, Data Engineering
Deliverable
production ML models | product features | infrastructure
Required skills
Multi-agent agentic AI system design, AWS GenAI (Bedrock AgentCore), Cloud architecture (AWS/Azure/GCP), Data architecture (Snowflake/BigQuery/Spark/Kafka), MLOps & model serving, Infrastructure as code (Terraform/CloudFormation), AI safety & responsible AI practices, RAG pipeline design, Cost optimization for LLMs
Preferred skills
Multi-cloud experience, Enterprise architecture certifications (TOGAF), AI ethics experience
Technologies
Amazon Bedrock AgentCore, AWS, Azure, GCP, Kubernetes, Docker, Lambda, EventBridge, Snowflake, Redshift, BigQuery, Spark, Kafka, SageMaker, Vertex AI, MLflow, Hugging Face, LangChain, LangGraph, CrewAI, AutoGen, PyTorch, TensorFlow, Terraform, CloudFormation, GitHub Actions, Airflow, Prefect, dbt, Claude Code, Cursor
Responsibilities
Define technical strategy and lead architectural design across cloud, data, and AI/ML systems; Architect and ship production-grade multi-agent agentic AI systems; Design and build scalable cloud-native solutions with a bias toward AWS; Design data architectures including warehouses, data lakes, and pipelines; Build and evolve scalable ML platforms and infrastructure; Drive performance, scalability, cost, and reliability optimization; Mentor and grow engineers at all levels; Partner with senior leadership and clients as the principal technical voice
Seniority
Principal, hands-on IC with strategy & mentorship