Principal AI Architect

Position Details

What you will do

• 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

Minimum Qualifications

• 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, GCP).
• 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

Benefits

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Potential Customer Requirements Notice

• To meet customer requirements and comply with local or state regulations, applicants for certain customer-facing roles may need to:
• - Undergo additional background screens and/or drug/alcohol testing for customer credentialing.

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