Position Overview:

As a Backend Software Engineer II at Diligent, you’ll take on a hands-on technical role in building secure, scalable, and high-performing applications and serverless microservices using TypeScript on AWS. You’ll contribute meaningfully to our mission of making governance effortless for our customers, working in a team that owns its applications and services end to end—from architecture and implementation to monitoring and continuous improvement.

This role is ideal for a mid-level engineer who writes solid code, mentors others, and embraces AI-powered tools to work smarter and faster. You’ll guide less experienced engineers, shape architectural discussions, and help scale modern development practices, including responsible use of AI in workflows.

Key Responsibilities

• Own and deliver well-defined stories independently, with a clear grasp of architecture, frameworks, and tools.

• Actively contribute to code reviews, testing practices, and maintain service stability across backend services and infrastructure components, collaborate with and mentor less experienced developers on patterns, fostering collaboration, knowledge sharing, and constructive feedback.

• Maintain healthy development flow by adhering to Agile processes and driving iterative enhancements.
  
  
• Use AI tools to accelerate backend development tasks like API design, database schema creation, infrastructure provisioning, debugging applications, and researching AWS best practices, always validating outputs and applying judgment. Understand core LLM concepts (e.g., tokens, context length, hallucinations), recognize safe vs. unsafe use cases, and flag ethical, privacy, or cost concerns.
  

Required Experience/Skills

• 3–5 years of professional software engineering experience in an agile, fast-paced environment.

• Familiar with core AI concepts (tokens, context length, embeddings, hallucinations), understands high-level LLM behavior, and recognizes safe vs. unsafe use cases (privacy, security, fairness). RAG or AWS Bedrock knowledge is a plus but not required.

• AI Tooling & Practices: Uses AI to boost productivity (e.g., test scenarios, architecture drafts, research), skilled in prompt engineering (instruction vs. few-shot), and evaluates AI outputs responsibly (bias, cost, ethics).

• Backend Proficiency: Strong experience with .NET (preferably .NET 8+) and Web API for REST API development, solid understanding of patterns, experience with ORMs, proficient with unit and integration testing, understands repository pattern and clean architecture principles. Python knowledge is a plus.

• Database & Data Management: Experience with SQL databases, willingness to learn about DB patterns and multi-tenant data isolation, basic knowledge of database performance optimizations, experience with data migration strategies. Basic understanding of vector databases for AI applications and NoSQL databases is a plus.

• Cloud & Infrastructure: Good understanding of AWS services (S3, API Gateway, Lambda, CloudFront and IAM), experience with Infrastructure as Code (like AWS CDK), understanding of serverless architecture patterns, knowledge of AWS security best practices.

• Security & Compliance: Solid understanding of .NET security practices including JWT authentication, API security, data encryption and secure coding practices.

• Performance & Reliability: Experience with performance optimization, understanding of caching strategies, knowledge of error handling and retry patterns, familiarity with monitoring and observability tools, understanding of scalability considerations.

• CI/CD mindset: Experience in CI/CD pipeline setup and exploring AI-assisted DevOps tooling.

• Collaboration & communication: Prioritizes team work over individual needs, comfortable discussing architectural decisions, documenting designs (potentially with AI assistance), and presenting technical ideas clearly.

• Growth Mindset: Willingness to gradually take on more complex challenges and learn new technologies.

#LI-Hybrid