Full Stack Engineer (Gen AI)

Ovise has partnered with a leading life insurance organization serving over 18 million customers across the US. This is an exciting opportunity to join a newly established AI practice, contributing to the development of next-generation applications while driving the adoption of AI across critical insurance functions.

As a key member of this team, you will design, build, and deploy scalable full-stack applications while integrating AI/ML solutions. If you have a strong background in full-stack development and are interested in expanding into AI/ML, this is a chance to work on high-impact, real-world applications in a highly regulated industry.

Responsibilities:

• Design, develop, and deploy full-stack applications with AI/ML capabilities.
• Build and maintain AWS-based infrastructure, ensuring security, scalability, and cost optimization
• Develop and integrate backend services using Python (Flask, FastAPI) and frontend applications with React and TypeScript
• Ensure seamless interaction between modern applications, legacy systems, and external APIs
• Implement CI/CD pipelines, automated testing, and DevOps best practices for production reliability
• Work with AI/ML teams to integrate models, optimize performance, and implement MLOps best practices
• Lead iterative development cycles using Agile methodologies

Qualifications:

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field.
• 8+ years of experience deploying and supporting full-stack applications in enterprise environments
• Strong expertise in frontend and backend development, including React, TypeScript, Python, Flask, SQL, and modern DevOps workflows
• Experience with AWS services such as Lambda, S3, SageMaker, Bedrock, and Infrastructure as Code (CDK)
• Familiarity with AI/ML concepts, MLOps, and model deployment techniques is a plus.
• Interest in Generative AI and a willingness to learn and integrate ML solutions into applications
• Ability to work in an Agile team, collaborating with engineers, data scientists, and business stakeholders