About the role: Agentic AI Architect We are seeking an Agentic AI Architect, to join Siemens Digital Industries Operations Software, to define the technical design of our Agentic AI platform and ensure the agent systems we build are coherent, scalable, and production-ready. The role focuses on architecture and system design - orchestration patterns, integration, reliability, and evaluation - for industrial-grade AI agent systems that augment and automate real business workflows in industrial operations. Once hired, your official title will be Platform Architect.
You will design how agentic systems are built end-to-end, from architecture and integration with existing services through to reliability, observability, and long-term operation. You will work closely with our headquarters architects in Germany to jointly shape the overall system architecture and core concepts, ensuring the Canadian team's work stays aligned with the global platform Working alongside product, platform, engineering, and domain experts, you will establish the patterns and standards that make our agentic capabilities trustworthy, scalable, and measurable and help shape how agentic systems are built across the organization. This is a hands-on architecture role: you will write design docs, review code, and make the technical decisions teams build on.
Architecture focus System design, orchestration patterns, integration, reliability, observability, evaluation, and long-term operation for industrial-grade agentic AI systems.
What will you do? - Define the architecture for scalable, industrial-grade agentic AI systems and the services around them
- Collaborate closely with headquarters architects in Germany on the overall system architecture and core concepts, contributing local input while keeping the platform coherent across sites
- Establish orchestration patterns for multi-agent coordination, agent communication, and AI interaction layers
- Design AI pipelines including RAG, evaluation, and quality-validation approaches
- Set standards for data ingestion, preprocessing, and transformation across the platform
- Define API and integration patterns for agent orchestration, data services, and connection to existing systems
- Drive architectural decisions on build-vs-adopt, framework selection, and long-term maintainability
- Set standards for reliability, error recovery, monitoring, and observability across AI workloads
- Guide performance, scalability, and cost optimization (compute, storage, inference) without compromising quality
- Establish governance, access control, and compliance patterns across AI workloads
- Collaborate with DevOps on CI/CD, deployment automation, and cloud/on-prem infrastructure design
- Partner cross-functionally with product, data science, engineering, and security to translate requirements into technical strategy
- Provide technical guidance and mentorship to engineers, helping raise the bar without becoming a bottleneck
What you will bring: - Master's degree or equivalent experience in Computer Science, Robotics, Artificial Intelligence, Software Engineering, or related fields.
- Over 8 years in AI/ML or software design/ development with 4+ years of experience in architecting AI platforms for agentic AI, robotics, industrial technology or automation.
- Strong background in Python backend development and microservices/distributed-systems architecture
- Solid understanding of LLMs, RAG pipelines, and prompt engineering
- Experience with agent application frameworks and multi-agent orchestration
- Experience designing on both cloud platforms and on-prem
- Hands-on experience with vector databases, knowledge graphs, and data pipelines
- Strong grasp of containerization, CI/CD, and cloud-native deployment (Docker, Kubernetes)
- Proven ability to design systems that multiple teams build on, balancing speed with long-term maintainability
What sets you apart: - Experience defining platform or reference architectures for 0-to-1 products that scaled
- Familiarity with AI observability tooling (e.g., Langfuse) and evaluation frameworks
- Knowledge of enterprise AI governance, performance tuning, and security
- Experience in regulated industries or enterprise platforms
- Experience with the NVIDIA AI stack (NeMo, NIM, Triton, Nemotron, NeMo Guardrails)
- Mendix or comparable low-code integration / extension experience
- Industrial / OT background - OPC-UA, MQTT, MES, historians, manufacturing data
- Enterprise integration experience (SAP, data fabric / streaming - Kafka)
- Open-source contributions or published work in the agentic-AI / LLM space
- Comfortable working across time zones and collaborating with distributed, international
Salary is commensurate with experience, and ranges between $ 140,000 CAD - $ 190,000 CAD, excluding bonus and benefits. In addition to base salary, this role includes eligibility for an annual discretionary bonus ranging from 10% to 15% of base salary, based on Company performance metrics.
