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IMO Health is looking for a Senior Full-Stack Software Engineer, AI Applications to design and deliver innovative AI-powered applications that enhance patient care and life sciences research, improving access to high-quality health information.

Requirements

• Proficiency in Java, Python, and JavaScript, with experience in frameworks such as Spring (IOC, Security, Boot) and frontend frameworks like React or Angular.
• Hands-on experience with cloud platforms (AWS/Azure), containerization (Docker, Kubernetes), and Infrastructure-as-Code (Terraform).
• Strong knowledge of relational databases (MySQL/PostgreSQL), performance optimization, and indexing strategies.
• Experience with Redis and Elasticsearch, including use in high-performance systems.
• Familiarity with AI/ML applications, including LLM integration and prompt engineering.
• Understanding of modern security practices, such as JWT and Zero Trust principles.
• Exposure to MLOps tools (e.g., SageMaker, Airflow, CI/CD workflows).

Responsibilities

• Develop and enhance AI-powered applications that support healthcare and life sciences innovation.
• Ensure applications meet performance, scalability, and security standards, troubleshooting issues as needed.
• Integrate AI/ML technologies, including Large Language Models (LLMs) and vector databases, into software solutions.
• Collaborate in an agile environment with cross-functional teams to align technical solutions with business needs.
• Participate in architectural and design discussions, providing input to ensure scalable, reliable, and secure solutions.
• Write clean, testable, and maintainable code following CI/CD and DevOps best practices.
• Contribute to automation efforts across testing, integration, and deployment pipelines.

Other

• 4+ years of experience in software development, ideally with exposure to AI-based applications.
• Strong problem-solving skills with the ability to balance technical quality and delivery needs.
• Collaborative mindset with the ability to work across teams and contribute to a culture of continuous learning.
• Experience in healthcare, clinical data, or life sciences NLP use cases.
• Contributions to open-source or academic research.