Build clean, scalable, and reliable solutions that support data-driven and AI-enabled environments
Develop and maintain clean, well-structured Python code with strong documentation and unit testing
Deploy, troubleshoot, and optimize applications in cloud environments using Docker and Kubernetes
Support and enhance CI/CD pipelines, improve automation, and deployment workflows
Collaborate with cross-functional teams, including scientists, data engineers, and ML engineers, to operationalize AI and analytical tools
Participate in code reviews, design discussions, and architectural improvements
Ensure reliability, performance, and scalability across production systems and services.

5+ years of professional software engineering experience
Proven track record of delivering production-quality applications in Python
Deep hands-on experience working with Docker, Kubernetes, and cloud platforms (with a strong preference for AWS)
Strong proficiency in Git, version control workflows, unit testing frameworks, and modern CI/CD tooling
Demonstrated ability to debug, troubleshoot, and resolve complex software, infrastructure, and deployment issues in production environments
Experience collaborating with multidisciplinary teams to deploy or support AI, machine learning, or scientific applications in real-world settings
Familiarity with large-scale, cloud-native infrastructures and the ability to apply best practices around reliability, observability, and system performance.

Software Engineer, Python

Key skills