What are the responsibilities and job description for the Mid Level Software Engineer, Full Stack position at Tential Solutions?
Job Profile: Mid Level Software Engineer, Full Stack
Responsibilities
Full Stack Development
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
- 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
- Lead code reviews, establish best practices, and contribute to architectural decisions
- Ensure all systems meet technology compliance, audit, cybersecurity, and data governance standards
- 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)
- 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
- 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