Engineering Team Leader

Description

We are seeking a highly skilled and motivated Team Leader to lead a multidisciplinary team of full-stack developers, QA engineers, and data analysts. The team will be responsible for developing the CytoReason Platform, a cutting-edge technology that revolutionizes drug R&D by enabling researchers to answer biological questions using computational AI models. As the Team Leader, you will play a crucial role in advancing CytoReason's mission to transform drug research and development. By leading the development of our innovative platform, you will empower researchers with the tools they need to make groundbreaking discoveries and improve patient outcomes.

Responsibilities

• Lead and manage a multi-disciplinary team, fostering a collaborative and high-performance work environment.
• Oversee the development and maintenance of the CytoReason Platform, ensuring it meets the highest standards of quality and performance.
• Collaborate with stakeholders to define project requirements, timelines, and deliverables.
• Provide technical guidance and mentorship to team members, promoting continuous learning and professional growth.
• Ensure the successful integration of backend, frontend, and algorithmic components.
• Monitor and optimize platform performance, scalability, and security.
• Stay up-to-date with industry trends and emerging technologies to drive innovation within the team.

Requirements

• +6 years of experience in leading and managing multi-disciplinary teams.
• Minimum of 10 years of experience in software development.
• Strong background in full-stack development, with expertise in Node.js (backend) and Vue.js (frontend).
• Proficiency in Python. • Experience with cloud hosting (GCP preferred), Kubernetes, and Docker.
• Excellent communication and leadership skills. • Ability to work effectively in a fastpaced, dynamic environment.
• Specific Technologies or tools: Backend: Node.js; Frontend: Vue.js; Algorithms: Python; Containerization: Kubernetes (k8s) and Dock.

Advantages

• Experience in the pharmaceutical or biotech industry.
• Knowledge of AI and machine learning models.
• Familiarity with data analysis and visualization tools.
• Understanding of biological research and drug development processes.
• Familiarity with R language.
• Experience with cloud hosting (GCP preferred), Kubernetes (k8s), and Docker.
• Experience with data pipelinesץ