Senior AI Backend Engineer: Scalable Cloud & Data Pipelines

Siemens Energy; Województwo mazowieckie; On-site; PLN 180,000 - 300,000; Full time

Benefits offered by this job

Career growth

Health and wellness benefits

Paid Time Off

Global team

Country-specific rewards

Job summary

Siemens Energy is seeking a senior backend engineer to design and develop scalable services and cloud-native applications that support AI/ML model deployment. You will transform AI prototypes into secure, production-ready solutions while partnering with AI, frontend, cloud, and platform teams to deliver enterprise-grade software.

Responsibilities include optimizing performance for AI inference, building robust data pipelines, and ensuring data quality and security within cloud environments.

Qualifications

• 5+ years of backend software engineering experience with scalable services
• Experience integrating and scaling AI/ML models in production
• Hands-on cloud (AWS/Azure) and containerized microservices

Responsibilities

• Design, build, and maintain scalable backend services and APIs to support AI/ML model deployment.
• Optimize backend performance for high-throughput AI inference and data retrieval.
• Develop and manage data pipelines for ingestion, preprocessing, and storage of procurement data.
• Establish CI/CD pipelines for automated testing, deployment, and monitoring of AI backend services.
• Collaborate with data scientists and analytics teams to ensure clean data delivery for AI training and inference.

Skills

Python

FastAPI

REST & gRPC

CI/CD

Cloud integration

Education

Bachelor's or Master's in CS/Software Engineering

Tools

Docker

Kubernetes

Terraform

Apache Airflow

Spark

Job description

Siemens Energy is seeking a senior backend engineer to design and develop scalable services and cloud-native applications that support AI/ML model deployment. You will transform AI prototypes into secure, production-ready solutions while partnering with AI, frontend, cloud, and platform teams to deliver enterprise-grade software.

Responsibilities include optimizing performance for AI inference, building robust data pipelines, and ensuring data quality and security within cloud environments.