Sr. Full Stack Software Engineer, AI Applications

WHAT YOU’LL DO:

• 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 Natural Language Processing (NLP), 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. 
• Share knowledge with peers and provide informal mentorship to junior engineers. 
• Proactively identify opportunities for improving system performance and addressing technical debt. 

WHAT YOU’LL NEED:

• 4+ years of experience in software development, ideally with exposure to AI/NLP-based applications. 
• Bachelor’s or Master’s degree in Computer Science, Software Engineering, AI, or a related field. 
• 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 service governance (e.g., Sentinel, Seata) and feature flag tools (e.g., LaunchDarkly) is a plus. 
• 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. 

NICE TO HAVE:

• Experience in healthcare, clinical data, or life sciences NLP use cases. 
• Exposure to MLOps tools (e.g., SageMaker, Airflow, CI/CD workflows). 
• Experience with cloud platforms (AWS, Azure). 
• Contributions to open-source or academic research.