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# commercial solution focused Principal AI Architect

- **Company:** Ecolab
- **Location:** Saint Paul, MN, United States
- **Experience:** Expert
- **Salary:** $166,300.0 - $249,600.0
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Amazon Web Services, Architectural Patterns, Microsoft Azure, Software as a Service, Cloud Computing, Computer Programming, Continuous Integration, Information Engineering, DevOps, Enterprise Architecture Framework, Github, Graph Database, Apache Hive, Python (Programming Language), OAuth, Role-Based Access Control, OpenAI, Data Mesh, Prometheus, Azure Machine Learning, Search Technologies, Workflow Management Systems, Zachman Framework, Google Cloud, Haystack, Microsoft Power Automate, Pytorch, LangChain, Retrieval-Augmented Generation, Large Language Models, Snowflake, Grafana, Multi-Agent Systems, Prompt Engineering, IT Architecture, Multi-Cloud, Agentic-AI, Togaf, Event Driven Architecture, Containerization, Data Lakes, Pyspark, Kubernetes, Information Technology, HuggingFace, Transformer Architectures, Graphql, Machine Learning Operations, Docker, Elk Stack, Databricks, Microservices
- **Published:** October 7, 2026
- **Apply:** https://www.dice.com/job-detail/d113f80a-93b8-4370-a2fc-3e13267232c6

## About the Role

* Bachelors Degree in Computer Science or related field and 10 years of experience in progressive architecture and AI/DS design and engineering
 * Enterprise Architecture: AI + data ecosystem design, multi-agent orchestration (LangChain, LangGraph, Haystack), enterprise-wide AI/ML standards.
 * AI/ML Platforms: LLM APIs (OpenAI, Hugging Face, Anthropic, MosaicML), transformer architectures, RAG workflows, LLMOps frameworks (prompt lifecycle, monitoring).
 * LLMOps frameworks (prompt lifecycle, monitoring, context engineering, harness engineering).
 * Data & Cloud Infrastructure: Databricks (Delta Lake, Spark SQL, PySpark, MLflow), Snowflake (enterprise-scale warehousing), Azure (AKS, Synapse, EventHub, Logic Apps).
 * Programming & Integration: Python (Transformers, LangChain, PyTorch), API integration (REST, GraphQL, gRPC), microservices/event-driven systems.
 * Governance & Security: Responsible AI frameworks, privacy/compliance, OAuth2, JWT, TLS, RBAC.
 * DevOps & Delivery: CI/CD (Azure DevOps, GitHub Actions), containerization (Docker, Kubernetes), observability (Prometheus, Grafana, ELK stack).
 * Leadership & Strategy: Influence technical strategy, mentor engineers, simplify complex concepts for diverse stakeholders.
 * Ability to thrive in an ambiguous environment, embracing change and utilizing proven reasoning in balancing practical business needs and architectural rigor
 * No immigration sponsorship is available for this role at this time.

Preferred Qualifications

 * Exposure to multi-cloud architectures (Azure, AWS, Google Cloud Platform).
 * Strong understanding of token-efficient AI consumption with an ability to surface FinOps tradeoffs
 * Experience with data mesh and federated AI systems.
 * Familiarity with knowledge graphs and semantic search.
 * Hands-on with MLOps orchestration tools (Kubeflow, MLflow, Vertex AI).
 * Understanding of edge AI deployment and IoT integration.
 * Experience in enterprise architecture frameworks (TOGAF, Zachman).
 * Knowledge of AI ethics frameworks and regulatory compliance (EU AI Act, ISO standards).
 * Demonstrated interconnected disciplinary knowledge of digital solution development

## Description

* Define enterprise architecture across GenAI, agentic workflows, ML platforms, and data engineering ecosystems.
 * Serve as a technical voice in leadership discussions, influencing strategy and navigating organizational challenges.
 * Architect and implement scalable AI solutions including agentic ecosystems, advanced pipelines, and AI model integrations with larger end-to-end SAAS solutions.
 * Evaluate and understand technologies that meet needs in support of cost optimized, multi-cloud solutions including aspects of Databricks, Snowflake, Azure and beyond.
 * Elevate governance standards covering security, compliance, and responsible AI/data use.
 * Mentor engineering teams, fostering autonomy, technical excellence, and architectural discipline.
 * Evaluate emerging AI/data tooling and integrate reusable architectural patterns to accelerate delivery.
 * Ensure alignment of architecture with business goals, scalability requirements, and innovation roadmaps.
 * Provide clear, consistent communication and presentation to various stakeholders related to AI architecture strategy and implementation to drive alignment, education and impact-based decisions
 * Work within an agile global resource model, planning for and delivering against initiatives, To meet customer requirements and comply with local or state regulations, applicants for certain customer-facing roles may need to