Backend Engineer (Node.js, TypeScript, AWS)

TL;DR

Backend Engineer (Node.js, TypeScript, AWS): Design, build, test, and improve backend services and APIs on secure, scalable microservices with an accent on production reliability at scale and cloud-native engineering on AWS. Focus on feature ownership from release through production support, while using AI tools responsibly to speed up research, coding, debugging, testing, and documentation.

Location: Hybrid — work onsite at least 50% of the time if within commuting distance to a Diligent office location.

Company

Diligent builds AI-driven governance, risk, and compliance (GRC) SaaS solutions for boards and executives.

What you will do

• Design, build, test, and improve backend services and APIs using Node.js, TypeScript, and AWS.
• Own well-defined features end-to-end, including code quality, deployment, and production support.
• Collaborate with product managers, designers, and engineers to turn requirements into practical, reliable solutions.
• Participate in technical design discussions, code reviews, and engineering standards.
• Use AI tools to accelerate research, coding, debugging, testing, and documentation while validating outputs.
• Improve security, observability, reliability, and day-to-day development practices.

Requirements

• 3 to 5 years of professional software engineering experience building production applications in an agile environment.
• Strong backend development skills with Node.js and TypeScript, including experience building APIs or microservices.
• Experience in a product engineering environment with React or Angular.
• Hands-on experience with AWS and cloud-native development, testing, and deployment practices.
• Comfort with SQL databases, Git, Docker-based workflows, and modern CI/CD pipelines.
• Practical understanding of AI-assisted engineering tools and responsible judgment regarding privacy, security, and quality.

Nice to have

• Familiarity with infrastructure as code (e.g., CDK or Terraform).
• Experience with observability tooling, incident response, or production monitoring.
• Broader understanding of LLM concepts (tokens, embeddings, hallucinations) and safe use cases.

Culture & Benefits

• Flexible work environment with a hybrid model and onsite expectation of at least 50% time for candidates within commuting distance to an office hub.
• Comprehensive health benefits, meeting-free days, generous time off, and wellness programs.
• Global days of service and support for learning and education through resources and programs.
• Teams across multiple global office locations and an emphasis on diversity and inclusion.

Hiring process

• Interview process includes technical evaluation through discussions of backend, cloud, and AI-assisted engineering practices.
• Code review and collaboration-focused conversations to assess communication and engineering standards.