AI Integration & Deployment Engineer

Siemens Gebze factory is the lead factory for Air Insulated Switchgear production in Siemens World and exporting to more than 80 countries worldwide! We are searching for a “AI Integration & Deployment Engineer”. You will join an exciting team and develop world-class solutions in a manufacturing facility. A great opportunity to experiment the harmony of code and real life!

The successful candidate will be responsible for integrating AI-driven solutions and large language models (LLMs) into existing digital platforms, ensuring secure, scalable, and efficient deployment within an industrial environment.

This position requires strong technical expertise in backend development, AI service integration, and deployment orchestration. The ideal candidate will play a key role in bridging artificial intelligence capabilities with enterprise-level systems to accelerate digitalization and automation initiatives.

Additionally, the role involves designing AI-driven data understanding layers — tagging, classifying, and enriching existing database records to enable semantic search and complex natural language queries across structured and unstructured data sources.

The engineer will help establish intelligent data pipelines that transform conventional SQL-based repositories into AI-accessible knowledge layers, supporting context-aware query generation and advanced analytics.

Responsibilities

– Design, implement, and maintain AI-powered integrations within enterprise digital platforms

– Develop RESTful APIs and backend microservices for connecting internal systems with AI services

– Manage the deployment lifecycle of AI components using Docker, Kubernetes, and CI/CD pipelines

– Build AI orchestration pipelines including prompt processing, intent mapping, and data retrieval mechanisms

– Ensure adherence to corporate standards on data privacy, access control, and cybersecurity

– Conduct functional and performance testing of deployed AI services

– Monitor and continuously optimize AI workloads in production environments

– Design data labeling and embedding strategies to make enterprise datasets searchable through AI.

Qualifications

– Bachelor’s or Master’s degree in Computer Engineering, Software Engineering, Electrical-Electronics, or Artificial Intelligence

– (Must have)Proven experience in delivering AI-driven integration or deployment projects in a production or enterprise environment, demonstrating measurable results or operational impact

– Proficiency in modern programming languages and frameworks commonly used for API and backend development (e.g., Python, JavaScript, or similar technologies)

– Hands-on experience with OpenAI, Azure OpenAI, Anthropic, or Hugging Face APIs

– Working knowledge of relational or analytical databases (e.g., MySQL, Snowflake)

– Understanding of vector databases (e.g., Pinecone, Weaviate, FAISS) and semantic search principles

– Experience working in secure, large-scale enterprise software environments

Preferred Skills

– Familiarity with prompt engineering and model tuning concepts

– Experience in transforming tabular and textual datasets into knowledge graphs or AI-queryable structures