Senior AI architect designing generative and agentic AI solutions for GE Vernova’s grid automation business. Leading cloud, edge, MLOps, and production deployment architecture.
About the role
- AI Foundation Architect designing secure, scalable enterprise AI foundations for Keyrus, which industrializes AI for business clients. Connecting cloud, data, applications, models, agents, and security.
Responsibilities
- Lead architecture discovery with clients to understand business objectives, existing systems, technical constraints, and AI requirements.
- Define target architectures for production AI and GenAI solutions, integrating models, agents, cloud services, enterprise data, applications, and APIs.
- Own key architecture decisions within the assigned scope, establishing reference patterns, technical boundaries, and design standards.
- Design secure and reliable foundations addressing identity, access, scalability, resilience, observability, and operational requirements.
- Evaluate architecture trade-offs, including model selection, performance, latency, infrastructure costs, and AI consumption patterns.
- Guide AI Engineers, Data Engineers, Software Engineers, and cloud specialists to ensure consistency across technical implementations.
- Advise client stakeholders, review technical designs, and document reusable architecture patterns and decisions.
- Convert successful architecture decisions into reusable Keyrus assets, including reference architectures, decision records, standards, patterns, and design guidance.
- Architect technical foundations connecting cloud infrastructure, data platforms, enterprise applications, models, agents, and security capabilities for scalable AI and agentic solutions.
Requirements
- Strong experience, 8 years +, designing and owning complex enterprise, solution, cloud, or data architectures in production environments.
- Recent experience architecting production GenAI, LLM, or agentic systems, including integration with enterprise applications and operational infrastructure.
- Experience defining reference architectures, technical standards, integration patterns, and architecture decisions.
- Experience designing distributed systems and enterprise integrations across multiple technical environments.
- Ability to evaluate architecture trade-offs involving security, reliability, scalability, performance, maintainability, and cost.
- Experience guiding multidisciplinary engineering teams and advising client architects, technical leaders, and business stakeholders.
- Deep architecture expertise in at least one major cloud ecosystem, such as AWS, Azure, or GCP, including relevant AI services.
- Experience designing architecture for model access and deployment patterns across managed AI services, APIs, open-source models, or comparable enterprise AI environments.
- Strong understanding of GenAI architectures, including LLMs, RAG, AI agents, model integration, and enterprise AI workflows.
- Experience with distributed systems, APIs, microservices, and enterprise integration patterns.
- Knowledge of enterprise data architectures, including lakehouse, streaming, data mesh, or feature stores.
- Understanding of security architecture, IAM, networking, resilience, observability, and production operations.
- Familiarity with MLOps, LLMOps, CI/CD, containers, infrastructure as code, and AI cost optimization.
- Nice to have: Experience with Amazon Bedrock, Azure AI, Vertex AI, or comparable cloud AI services.
- Nice to have: Experience designing multi-agent systems, model routing, or AI orchestration architectures.
- Nice to have: Familiarity with LangGraph, MCP, AI gateways, or similar technologies.
- Nice to have: Experience with Terraform, Kubernetes, or enterprise infrastructure automation.
- Nice to have: Experience with regulated environments, AI governance, or formal architecture review processes.
- Nice to have: Consulting or professional services experience across multiple clients.
- Strong technical judgment, clear communication, problem-solving, and leadership skills.
Benefits
- A stimulating environment where you can challenge yourself and discover new horizons.
- A strong culture of innovation and entrepreneurship.
- Opportunities to celebrate success through team activities, social events, and special celebrations.
- Comprehensive group insurance for you and your family.
- RRSP and DPSP participation plans.
- Monthly wellness allowance.
- Telecommunication reimbursement.
- 4 weeks of paid vacation.
- Language courses (French and English).
- Access to continuous learning through certifications, conferences, training programs, and industry events.
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