Lead Full Stack Developer

Project Description

• Design and develop full stack applications supporting regulatory workflows, data analysis, and reporting
• Build performant, secure RESTful and GraphQL APIs using modern backend frameworks (Java/Spring Boot)
• Basic Knowledge of Python/FastAPI is a bonus
• Develop responsive, accessible frontends using Angular and TypeScript
• Collaborate with data engineers, security teams, and business analysts to translate regulatory requirements into technical solutions
• Responsibly adopt and leverage AI-assisted development tools (Kiro) while maintaining code quality standards and information security hygiene
• Automated quality assurance, CI/CD
• Architect and maintain CI/CD pipelines using tools such as GitHub Actions, GitLab CI, or Jenkins
• Implement infrastructure-as-code and containerized deployments (Docker, Kubernetes)
• Implement and integrate automated testing (unit, integration, E2E) and security principles into delivery pipelines
• Process for more senior
• Mentor junior and mid-level engineers through code reviews, pair programming, and knowledge sharing
• Ensure all systems meet technology compliance, audit, cybersecurity, and data governance standards

Required Qualifications

• 7+ years of professional software engineering experience, with at least 1-2 years in a senior capacity
• Strong proficiency in one or more backend languages: Python, or Java
• Deep experience with modern frontend frameworks (Angular) and TypeScript
• Hands-on experience designing and operating CI/CD pipelines end-to-end
• Solid understanding of containerization (Docker), AWS Lambda, and orchestration (Kubernetes, ECS)
• Experience with AWS and managed services
• Familiarity with relational databases PostgreSQL and NoSQL stores
• Strong understanding of application security principles (OWASP Top 10, secrets management, least-privilege access)
• Experience with version control workflows (Git, trunk-based development, or GitFlow)
• Practical experience integrating AI/ML models or LLM APIs (e.g. AWS Bedrock) into production applications
• Demonstrated understanding of why human oversight of AI systems is critical in high-consequence domains

Preferred Qualifications

• Experience in a regulatory, or financial services environment
• Experience building human-in-the-loop review systems, annotation platforms, or approval workflows for AI outputs
• Familiarity with event-driven architectures and messaging systems (Kafka, AWS SQS/SNS)
• Exposure to observability tooling (Datadog, Grafana) including AI/ML model monitoring
• Experience with feature flagging, canary deployments, or progressive delivery strategies
• Contributions to open-source projects or internal developer platform tooling