Mid Level Software Engineer, Full Stack

Job Profile: Mid Level Software Engineer, Full Stack Responsibilities Full Stack Development Design and develop scalable full stack applications with Angular frontends and microservices-based backends Build performant, secure RESTful and GraphQL APIs using modern backend frameworks (Java/Spring Boot, Python/FastAPI) 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 (AWS Kiro or others) while maintaining code quality standards and information security hygiene CI/CD & Infrastructure Design and maintain CI/CD pipelines using tools such as Jenkins and Gitlab Implement infrastructure-as-code and containerized deployments for AWS services like Fargate and Lambda Integrate automated testing (unit, integration, E2E) and security principles into delivery pipelines General Engineering Skills Lead code reviews, establish best practices, and contribute to architectural decisions Ensure all systems meet technology compliance, audit, cybersecurity, and data governance standards Required Qualifications Bachelor's degree in Computer Science, Software Engineering, or related field 5-7 years of professional software engineering experience Strong proficiency in backend languages: Python and/or Java 3+ years of production experience with Angular (latest versions), TypeScript, RxJS, and state management (NgRx) Experience designing and implementing RESTful APIs and/or GraphQL services Hands‑on experience with AWS services (Lambda, ECS, API Gateway, S3, RDS, DynamoDB) and containerization (Docker) Proficiency with both relational (PostgreSQL) and NoSQL (MongoDB, DynamoDB) databases Solid understanding of application security principles (OWASP Top 10, secrets management, least‑privilege access) Preferred Qualifications Experience in 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, Kinesis) Exposure to observability and log tooling (Splunk, Datadog, Grafana, CloudWatch) including AI/ML model monitoring Experience with microservices patterns (circuit breakers, service mesh, distributed tracing) Experience with feature flagging, canary deployments, or progressive delivery strategies Contributions to open‑source projects or technical publications in AI/ML domains Key Competencies End‑to‑end ownership of features from UI to database Strong debugging and troubleshooting skills across the full technology stack Strong understanding of RESTful APIs and supporting API‑driven platforms Ability to balance business needs, technical constraints, and scalability Excellent collaboration and communication skills with cross‑functional teams Strong commitment to automated testing and code quality #J-18808-Ljbffr Tential Solutions