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# Principal AI Systems Architect

- **Company:** AllSTEM Connections
- **Location:** Ontario, CA, United States
- **Experience:** Expert
- **Contract:** Temporary contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Systems Engineering, Databases, Continuous Integration, Distributed Systems, Software Safety, Systems Architecture, Data Ingestion, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, IT Architecture, Generative AI, Web Filtering, Containerization, Machine Learning Operations
- **Published:** July 17, 2026
- **Apply:** https://www.dice.com/job-detail/44a906f1-0eca-4055-84a0-a42c791b90ce

## About the Role

Experience Baseline: 10+ years of software/systems engineering; 6+ years specifically focused on AI/ML in production.
Systems Architecture: Demonstrated success in designing end-to-end AI systems-from data ingestion through monitoring-at scale.
GenAI Proficiency: Expert knowledge of production GenAI (LLM providers, vector databases, and observability tools like LangSmith/LangFuse).
Communication: Ability to produce clear, durable technical artifacts (design records, architectural diagrams) that allow a team to execute a complex vision autonomously.
Collaboration: Experience working in an "embedded team" model; comfortable facilitating design workshops and providing direct technical feedback.

Preferred Attributes
Experience operationalizing AI in highly technical or regulated environments (e.g., critical infrastructure, industrial automation, or complex hardware-interfaced systems).
Proficiency in containerization, CI/CD, and instrumenting AI systems in production.
Experience implementing AI safety, content filtering, and governance guardrails.

## Description

We are seeking a Principal AI Systems Architect for a focused, time-boxed engagement to define the foundational AI architecture for our core product platform. You will embed directly within our engineering team to design, validate, and document the architectural assets and deployment playbooks necessary to transition our current infrastructure into an autonomous, AI-native environment.
This is a high-autonomy role for a seasoned AI leader who thrives on "blank slate" architectural design and wants to leave a lasting, high-impact blueprint for an engineering team to execute against. You will not be an outside consultant; you will be a full team member, driving the vision for cloud-to-edge AI deployment and defining how we operationalize GenAI at production scale., Architectural Leadership
AI Reference Architecture: Develop and validate a production-grade AI reference architecture that spans data ingestion, inference, and monitoring across distributed environments.
Playbook Engineering: Produce "immediately usable" deployment playbooks, decision records, and technical artifacts that provide clear, durable guidance for our engineers.
System Design: Architect solutions for edge-to-cloud execution, balancing latency, cost, and resiliency. Define the standards for time-series data handling, event-driven integration, and API patterns.

GenAI & MLOps Governance
GenAI Orchestration: Design production-scale GenAI applications utilizing agentic architectures, multi-agent orchestration, and complex tool-calling patterns.
MLOps/Observability: Establish robust MLOps foundations, including model versioning, drift detection, observability, and cost-optimization strategies (routing, caching, and model selection).
RAG & Retrieval: Architect production-scale RAG (Retrieval-Augmented Generation) pipelines, vector database strategies, and embedding models that ensure high-performance, accurate retrieval.


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