You’ll help power the AI agents that support Siemens Energy teams by building the production infrastructure they depend on every day. Working within the AI Factory, you will create scalable, secure, and repeatable platforms that enable rapid deployment of new AI agents and models. From infrastructure-as-code and observability to CI/CD and runtime optimisation, you’ll ensure AI services remain reliable, efficient, and cost-effective as adoption grows. Partnering closely with a Senior Architect, you’ll contribute to a platform designed to support agent teams across Gas Services while helping shape the future of AI at a company with a 150-year engineering legacy.
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Build and maintain production-grade AI infrastructure using Infrastructure as Code (Terraform/CDK), monitoring, logging, and deployment automation to enable fast and secure agent delivery.
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Optimise the performance and cost efficiency of LLM workloads through autoscaling, caching, batching, and infrastructure right-sizing strategies.
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Develop and maintain CI/CD pipelines tailored for AI workloads, including model and prompt versioning, automated testing, and rollback mechanisms.
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Support agent-tool integration patterns using MCP and production infrastructure, ensuring consistent authentication, auditing, reliability, and performance.
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Create platform documentation, runbooks, self-service tooling, and automated alerting capabilities that improve developer experience and operational excellence.
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Monitor, troubleshoot, and respond to production incidents while implementing self-healing capabilities across AI infrastructure.
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Approximately 5 years of experience in cloud infrastructure or platform engineering, including supporting AI/ML workloads in production environments.
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Strong expertise with AWS services, including ECS, Lambda, API Gateway, and Bedrock Agent Core.
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Hands-on experience with Infrastructure as Code solutions such as Terraform or CDK.
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Solid knowledge of containerised environments including Docker and Kubernetes, as well as CI/CD pipelines for backend or machine learning systems.
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Experience with monitoring and observability tools, along with the ability to quickly diagnose and resolve production issues.
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Interest in or experience working with LLM serving, vector databases, and the operational requirements of AI platforms.
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University degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
You will join the AI Factory team, working closely with platform and architecture specialists who are focused on enabling the successful deployment and operation of AI agents at scale. The team is dedicated to building reliable, secure, and efficient AI infrastructure that supports innovation across Gas Services while maintaining the high engineering standards associated with Siemens Energy.
At Siemens Energy, we are more than just an energy technology company. With over 100,000 dedicated employees in more than 90 countries, we develop the energy systems of the future, ensuring that the growing energy demand of the global community is met reliably and sustainably. The technologies created in our research departments and factories drive the energy transition and provide the base for one sixth of the world’s electricity generation.
Our global team is committed to making sustainable, reliable, and affordable energy a reality by pushing the boundaries of what is possible. We uphold a 150-year legacy of innovation that encourages our search for people who will support our focus on decarbonization, new technologies, and energy transformation.
Find out how you can make a difference at Siemens Energy: Employee Video
At Siemens Energy, we celebrate diversity and inclusion and believe our strength comes from different backgrounds, experiences, and perspectives. We are committed to creating a workplace where everyone can thrive, contribute, and be valued for who they are.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
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Competitive salary and meal allowance
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Fair compensation for international work
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Health insurance coverage
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Remote work permitted within the country
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Additional 5 “Pontes” days off and Birthday off if it falls on a weekday, when not abroad (only applies for Portugal)
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Among others
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