Staff Software Architect

Job Description Summary The ideal candidate will have a technical background in AI engineering, data engineering, and AWS cloud computing, with excellent problem-solving skills, and a passion for designing innovative solutions. As a Staff Software Architect, You will be responsible for architecting and overseeing the development of complex software systems, ensuring they meet business requirements and leverage the latest technologies.

GE Healthcare is a leading global medical technology and digital solutions innovator. Our mission is to improve lives in the moments that matter. Unlock your ambition, turn ideas into world-changing realities, and join an organization where every voice makes a difference, and every difference builds a healthier world. Job Description

• Architect and design scalable, reliable, and secure software solutions using AWS cloud services.
• Lead AI engineering projects, integrating machine learning models and algorithms into software applications.
• Develop and maintain data pipelines and ETL processes to support data engineering initiatives.
• Collaborate with cross-functional teams to gather requirements and define technical specifications.
• Ensure the integration of AI and data engineering solutions into the overall system architecture.
• Conduct code reviews and enforce best practices for software development and architecture.
• Monitor and optimize system performance, ensuring high availability and scalability.
• Stay up-to-date with industry trends and emerging technologies, applying them to improve existing systems.
• Provide technical leadership and mentorship to engineering teams.
• Document architectural decisions and technical specifications for future reference.

• Bachelors Degree in Computer Science or STEM Majors (Science, Technology, Engineering and Math) with a minimum of 10+ years of advanced experience in technical capabilities.
• Proven experience as a software architect or in a similar senior technical role.
• Proficient technical background with expertise in AI engineering and AWS cloud computing.
• Experience with data engineering and ETL processes.
• Experience with big data technologies (e.g., Hadoop, Spark).
• Knowledge of microservices architecture and distributed systems.
• Proficiency in programming languages such as Python, Javascript, Go or Rust.
• Experience with AWS services including EC2, S3, Lambda, RDS, and SageMaker.
• Knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes).
• Familiarity with DevOps practices and tools (e.g., Git, Jenkins, Terraform).
• Experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack).
• Familiarity with software engineering principles and best practices (e.g., version control, testing, debugging).
• Understanding of machine learning concepts and algorithm and Knowledge of machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn.
• Understanding of Large Language Models (LLM) and Foundation Models (FM).
• Excellent problem-solving skills and the ability to troubleshoot complex issues.
• Good communication and collaboration skills.
• Ability to work effectively in a fast-paced and dynamic environment.
• Experience with Agile methodologies and project management tools.
• Certification in relevant technologies or methodologies (e.g., AWS Certified Machine Learning Specialty, Kubernetes Certified Administrator).
• Certification in machine learning or related fields.

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