Senior Backend & AI Platform Engineer

As a Senior Backend & AI Engineer with 6+ years of experience, you will play a crucial role in leading the development and scaling of the Agentic AI platform. Your focus will be on strong backend engineering, AI/ML engineering, pipeline ownership, data processing, and production hardening. Key Responsibilities: - Design and develop scalable backend services using Python (FastAPI/Flask). - 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. - Drive platform hardening including performance optimization, monitoring, and observability. - Collaborate with DevOps teams on CI/CD, deployment automation, and cloud infrastructure. - Support transition from vendor to Siemens Energy ownership and ensure long-term scalability. - Ensure platform reliability, uptime, and scalability using SRE and DevOps best practices. - Optimize compute, storage, and inference costs while maintaining performance and quality. - Establish strong governance, access control, and compliance processes across AI workloads. - Collaborate cross-functionally with product, data science, engineering, and security to deliver high-impact AI features and integrations. - Troubleshoot production issues and continuously improve the platforms architecture and performance. Technical Skills: - Strong expertise in Python backend development and microservices architecture. - Experience with LLMs, RAG pipelines, and prompt engineering. - Working experience on Agent application frameworks and on LLM model fine-tuning. - Hands-on experience with vector databases, knowledge graphs, and data pipelines. - Experience with Azure cloud services (Azure OpenAI preferred). - Knowledge of containerization, CI/CD, and distributed systems. Additional Preferred Skills: - Experience with multi-agent systems or orchestration frameworks. - AI observability tools (e.g., Langfuse) experience. - Knowledge of enterprise AI governance, performance tuning, and security. - Experience in regulated industries or enterprise platforms. As a Senior Backend & AI Engineer with 6+ years of experience, you will play a crucial role in leading the development and scaling of the Agentic AI platform. Your focus will be on strong backend engineering, AI/ML engineering, pipeline ownership, data processing, and production hardening. Key Responsibilities: - Design and develop scalable backend services using Python (FastAPI/Flask). - 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. - Drive platform hardening including performance optimization, monitoring, and observability. - Collaborate with DevOps teams on CI/CD, deployment automation, and cloud infrastructure. - Support transition from vendor to Siemens Energy ownership and ensure long-term scalability. - Ensure platform reliability, uptime, and scalability using SRE and DevOps best practices. - Optimize compute, storage, and inference costs while maintaining performance and quality. - Establish strong governance, access control, and compliance processes across AI workloads. - Collaborate cross-functionally with product, data science, engineering, and security to deliver high-impact AI features and integrations. - Troubleshoot production issues and continuously improve the platforms architecture and performance. Technical Skills: - Strong expertise in Python backend development and microservices architecture. - Experience with LLMs, RAG pipelines, and prompt engineering. - Working experience on Agent application frameworks and on LLM model fine-tuning. - Hands-on experience with vector databases, knowledge graphs, and data pipelines. - Experience with Azure cloud services (Azure OpenAI preferred). - Knowledge of containerization, CI/CD, and distributed systems. Additional Preferred Skills: - Experience with multi-agent systems or orchestration frameworks. - AI observability tools (e.g., Langfuse) experience. - Knowledge of enterprise AI governance, performance tuning, and security. - Experience in regulated industries or enterprise platforms.