Jobs / Siemens
Senior Agentic AI Software Backend & Platform Engineer
Siemens · Kitchener, ON, Canada
Kitchener, ON, CanadaExp: 4+ yrs125,000-175,000 CAD/yearlyHybrid
Remuneration
$125,000–$175,000 CAD base salary, plus eligibility for an annual discretionary bonus of 10% and health and wellness benefits
Location
Kitchener, ON, Canada
Visa sponsorship
Not specified
Job summary
Develop and scale an agentic AI platform for industrial operations, owning backend services, AI pipelines, data processing, and production reliability from architecture through ongoing operation. Build orchestration systems and APIs, tune and evaluate RAG workflows, and strengthen observability, governance, security, and cost efficiency using Python, cloud services, Docker, Kubernetes, and related AI technologies.
Benefits
Health and wellness benefitsEligibility for an annual discretionary bonus of 10%
Qualifications
- At least 4 years of experience developing and scaling AI platforms.
- Strong Python backend development and microservices experience.
- Experience with LLMs, RAG pipelines, and prompt engineering.
- Experience with agent application frameworks and LLM fine-tuning.
- Hands-on experience with vector databases, knowledge graphs, and data pipelines.
- Experience with cloud services; AWS preferred.
- Knowledge of containerization, CI/CD, and distributed systems.
- Understanding of cloud-native and on-premises deployment, including Docker, Kubernetes, and the NVIDIA AI stack.
- Master’s degree or equivalent experience in a related technical field.
Responsibilities
- Design and develop scalable backend services for agentic AI orchestration and execution.
- Own AI pipelines, including RAG tuning, evaluation, and quality validation.
- Build and maintain data ingestion, preprocessing, and transformation pipelines.
- Implement APIs for agent orchestration, data services, and AI interaction layers.
- Improve platform performance, monitoring, and observability.
- Collaborate with DevOps teams on CI/CD, deployment automation, and cloud infrastructure.
- Ensure platform reliability, uptime, and scalability using SRE and DevOps practices.
- Optimize compute, storage, and inference costs while maintaining performance and quality.
- Establish governance, access control, and compliance processes for AI workloads.
- Troubleshoot production issues and improve platform architecture and performance.
- Collaborate with product, data science, engineering, and security teams on AI features and integrations.
Skills
AWSDockerKafkaKubernetesPython
Degrees
Master’s degree or equivalent experience in Computer Science, Robotics, Artifici
Industry
Industrial operations softwareManufacturing
Relocation
No