Prototype agentic AI systems

Explore AI-native approaches using frameworks such as AWS Bedrock, EPAM Codemie, and open tools

Apply prompt and context engineering techniques to optimize insurance-specific workflows

Develop sample POCs, including Synthetic Personas and automated enterprise agentic networks

Automate context engineering pipelines to streamline processes

3+ years experience in Python, Node.js, TypeScript, and Java for generative AI application development

Knowledge of TensorFlow/PyTorch for AI experimentation

Background in AWS services such as Lambda, API Gateway, and VPC

Competency in event-driven architecture and REST/GraphQL API design, with proficiency in Kafka

Proficiency with Docker and Kubernetes for containerization

Experience with serverless frameworks and AI tools like Claude Code and GitHub Copilot

Solid qualifications in NoSQL/SQL databases (e.g. MongoDB, DynamoDB, PostgreSQL)

Showcase of reliable unit and integration testing practices

Expertise in CI/CD automation using GitHub Actions, Jenkins, or GitLab

Familiarity with security best practices for developing secure software solutions

Capability to work both independently and collaboratively within a team setting