Principal Full Stack Engineer

About the job

Bachelor's degree in technical or business discipline. Minimum 8+ years of Full Stack Engineering experience, including demonstrated experience as a technical lead or principal engineer. Deep expertise in applying object-oriented design patterns, architectural patterns, and distributed systems principles. Advanced proficiency with TypeScript, React, Node.js, AWS Lambda, AWS S3, SQL, Spring Boot, GitHub Actions. Experience with GitHub Copilot or similar products such as Claude Code, including driving adoption of AI-assisted development practices across teams. Proven track record architecting, delivering, and supporting multiple complex, large scale production applications. Expert knowledge of IT concepts, strategies, and methodologies, with the ability to set technical direction across teams. Demonstrated experience leading engineering teams technically, mentoring engineers, and driving adoption of best practices. Deep experience with Agile methodologies (e.g., Scrum) and scaling engineering practices. Expertise designing and optimizing CI/CD pipelines and tooling, and defining testing frameworks, strategies, and best practices. Proven ability to influence stakeholders and drive alignment across engineering, product, and business partners. Exceptional analytical, problem-solving, and decision-making skills, with strong ownership and initiative. Excellent oral and written communication skills, including the ability to communicate complex technical concepts to technical and nontechnical audiences. Team-oriented leader, with strong collaboration, prioritization, and adaptability skills. Understanding of AI/ML concepts and how they apply to software product development at scale. Experience architecting and integrating Large Language Model (LLM) APIs (e.g., OpenAI, Azure OpenAI, AWS Bedrock) into production applications. Hands-on experience with Retrieval-Augmented Generation (RAG) patterns, including vector databases and embedding models. Experience designing solutions with AI orchestration frameworks. Expertise in prompt engineering techniques and best practices for building reliable, production-grade AI-driven features. Understanding of responsible AI principles, including bias awareness, explainability, and data privacy considerations. Experience designing, building, or consuming AI-powered APIs and microservices in a cloud-native environment (AWS preferred).