Software Engineer for AI Application Development and Operations

About the Role

Location Romania Bucuresti Bucharest Remote vs. Office Hybrid (Remote/Office) Company Siemens Energy Organization Grid Technologies Business Unit Product Management Full / Part time Full-time Experience Level Mid-level Professional

A Snapshot of Your Day

As a Software Engineer for AI Application Development and Operations, you will develop and operate internal AI applications in collaboration with our data science and Azure cloud infrastructure teams, ensuring stability, security, and scalability across our enterprise environment. As one of the first members of a newly forming team, you will help establish development standards and operational practices within our small, agile teams that prioritize ownership, speed, and collaboration. Your expertise in software engineering, AI application development, machine learning operations, and cloud DevOps will be crucial for implementing best practices and delivering high-impact, production-ready AI solutions on our Azure infrastructure.

How You’ll Make an Impact

Transition data science proof-of-concept models into secure, scalable, production-ready solutions, and ensure their reliable operation. Design, develop, and operate AI applications on Azure Cloud infrastructure. Build and maintain CI/CD pipelines tailored for AI workloads, enabling seamless integration and continuous delivery. Monitor AI application performance, availability, and security, and proactively resolve issues to ensure reliable operations. Apply software engineering best practices to AI application development, including modular design, version control, and automated testing. Establish and promote best practices for AI application lifecycle management, including deployment, rollback strategies, and observability. Collaborate with cross-functional teams to align AI solutions with business requirements and operational goals. Develop containerized microservices for AI applications using Docker and manage them via Azure Container Services. Set up and manage AI application endpoints, ensuring secure access and efficient scaling. Contribute to the continuous improvement of development and operations processes for AI applications.

What You Bring

Strong communication and interpersonal skills, with the ability to collaborate effectively in small, agile teams and contribute to a positive and productive team culture. Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field. Proven experience in software engineering with a focus on applicationdesign, development, and operations. Strong proficiency in Python, including experience with common machine learning libraries such as PyTorch, and scikit-learn. Solid understanding of the AI/ML lifecycle, including model deployment, monitoring, and scaling in production environments. Experience in designing, developing, and integrating APIs, especially for serving AI models and enabling internal tool integration. Hands-on experience with development on cloud infrastructure, ideally Azure. Familiarity with security best practices, performance monitoring, and troubleshooting in cloud-based environments. Strong grasp of version control, branching strategies, and release management. Excellent problem-solving skills and the ability to work both independently and collaboratively in cross-functional, international teams. Experience with frontend development and prior knowledge of LLM frameworks like LangChain or LlamaIndex are not mandatory but would be advantageous.