Diligent Corporation
SaaS
SoftwareEngineer(Node.js)
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“Software Engineer (Node. js) at Diligent Corporation. Skills: Node.js, TypeScript, AI, Microservices. Deliver technical contributions. Own smaller user stories”
Industry & Context.
Debugging
What They're Looking For.
Must Have
0–3 years software development, Familiar with core AI concepts, Familiar with AI terminology, Awareness of AI-powered coding tools, Familiarity with Node.js, Familiarity with TypeScript, Familiarity with React, Understanding of Git, Experience with Docker
Nice to Have
Growth mindset in AI, Can name common AI tools, Describe general AI tool use, Understand AI outputs are probabilistic, Awareness of integrating AI tools, Emphasis on reviewing AI outputs, Emphasis on refining AI outputs, Awareness of data privacy, Awareness of compliance using AI tools, Knows not to share proprietary information, Knows not to share sensitive information, Can flag privacy issues, Can flag safety issues, Can flag fairness issues
What You'll Do.
Deliver technical contributions
Own smaller user stories
Partner with senior engineers
Experiment with AI techniques
Contribute to agentic workflows
Contribute to LLM features
Follow engineering best practices
Contribute to team flow
Use AI tools to accelerate coding
Use AI tools to accelerate debugging
Use AI tools to accelerate testing
Use AI tools to accelerate research
Use AI tools to accelerate code reviews
Apply judgment to AI outputs
How You'll Work.
Team & Collaboration
Risk Manager product team; Architectural discussions; Sprint demos
Process & Methodology
Agile environment
Full Job Description
Position Overview: As a Software Engineer I at Diligent, you'll help build and evolve our Risk Manager platform — a core product in Diligent's GRC suite that helps organizations identify, assess, and mitigate risk. You'll develop secure, scalable microservices using TypeScript and React in a serverless architecture on AWS, and contribute to AI-powered features that transform how customers manage risk. Working within the Risk Manager product team, you’ll take end-to-end ownership of services, from development to deployment and monitoring. You’ll be part of architectural discussions, actively contribute to sprint demos, and gain exposure to the full product lifecycle. This role is perfect for someone early in their engineering journey who is eager to grow, build real AI/agentic features, and make a meaningful impact from day one. Key Responsibilities Deliver technical contributions on early-career tasks with growing autonomy. Own smaller user stories independently; partner with senior engineers on more complex projects. Demonstrate curiosity and a growth mindset — experiment with emerging AI techniques, contribute to agentic workflows and LLM-powered features as part of the product. Follow engineering best practices (code quality, testing, CI/CD) and contribute to a healthy team flow. Use AI tools to accelerate coding, debugging, testing, research, and code reviews, always validating outputs and applying judgment. Required Experience/Skills 0–3 years of hands-on software development in an agile environment. Growth mindset in AI: Familiar with core AI concepts and terminology (machine learning, large language models, generative AI). Can name common tools (e.g., ChatGPT, GitHub Copilot, Cursor) and describe their general use. Understands that AI outputs are probabilistic and must be validated, not taken as facts. Knowledge of AI-powered coding tools: Awareness of how to integrate tools like GitHub, Copilot, Cursor, or similar into daily tasks, with an emphasis on review
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