Siemens Digital Industries Software is a leading provider of solutions for the design, simulation, and manufacture of products across many different industries. Formula 1 cars, skyscrapers, ships, space exploration vehicles, and many of the objects we see in our daily lives are being conceived and manufactured using our Product Lifecycle Management (PLM) software.  

We are seeking AI Backend Engineers to play a pivotal role in building our Agentic Workflow Service and Retrieval-Augmented Generation (RAG) Service. In this hybrid role, you'll leverage your expertise in both backend development and machine learning to create robust, scalable AI-powered systems using AWS Kubernetes, Amazon Bedrock models, AWS Strands Framework, and LangChain / LangGraph.  

   

Understanding of and expertise in:  

Design and implement core backend services and APIs for agentic framework and RAG systems  LLM-based applications using Amazon Bedrock models  RAG systems with advanced retrieval mechanisms and vector database integration  Implement agentic workflows using technologies such as AWS Strands Framework, LangChain / LangGraph  Design and develop microservices that efficiently integrate AI capabilities  Create scalable data processing pipelines for training data and document ingestion  Optimize model performance, inference latency, and overall system efficiency  Implement evaluation metrics and monitoring for AI components  Write clean, maintainable, and well-tested code with comprehensive documentation  Collaborate with multiple cross-functional team members including DevOps, product, and frontend engineers  Stay current with the latest advancements in LLMs and AI agent architectures  

   

Minimum experience requirements  

6+ years of total software engineering experience  Backend development experience with strong Python programming skills  Experience in ML/AI engineering, particularly with LLMs and generative AI applications  Experience with microservices architecture, API design, and asynchronous programming  Demonstrated experience building RAG systems and working with vector databases  LangChain/LangGraph or similar LLM orchestration frameworks  Strong knowledge of AWS services, particularly Bedrock, Lambda, and container services  Experience with containerization technologies and Kubernetes  Understanding of ML model deployment, serving, and monitoring in production environments  Knowledge of prompt engineering and LLM fine-tuning techniques  Excellent problem-solving abilities and system design skills  Strong communication skills and ability to explain complex technical concepts  Experience in Kubernetes, AWS Serverless  Experience in working with Databases (SQL, NoSQL) and data structures   Ability to learn new technologies quickly   

  

Preferred Qualifications:  

Must have AWS certifications - Associate Architect / Developer / Data Engineer / AI Track  Must have familiarity with streaming architectures and real-time data processing  Must have experience with ML experiment tracking and model versioning  Must have understanding of ML/AI ethics and responsible AI development  Experience with AWS Strands Framework  Knowledge of semantic search and embedding models  Contributions to open-source ML/AI projects  

 We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status.  

We are Siemens  

A collection of over 377,000 minds building the future, one day at a time in over 200 countries. We're dedicated to equality, and we welcome applications that reflect the diversity of the communities we work in. All employment decisions at Siemens are based on qualifications, merit, and business need. Bring your curiosity and creativity and help us shape tomorrow! We offer a comprehensive reward package which includes a competitive basic salary, bonus scheme, generous holiday allowance, pension, and private healthcare.  

Siemens Software. ‘Transform the everyday'  

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