Software Engineer AI - Multiple Levels

Diligent Corporation•Vancouver, BC

19h•CA$100,000 - CA$150,000•Hybrid

About The Position

As a Software Engineer on Diligent's Platform AI team, you'll help design, build, and operate the core services that power AI-driven capabilities across Diligent's global product suite. You'll build secure, scalable, serverless services on AWS that translate AI research and models into commercial-quality, production-ready solutions — enabling customers to derive insights from their governance data. You'll work closely with AI researchers, product managers, and other engineering teams, owning your services end-to-end: architecture, implementation, deployment, and monitoring. The team operates with a strong AI-augmented engineering culture — using AI tools to accelerate coding, testing, debugging, and delivery — while applying sound judgment about when and how to apply them.

Requirements

Professional software engineering experience building web applications in an agile environment (see level modifiers for years).
Hands-on experience with AWS services; familiarity with infrastructure as code (CDK, Terraform, or similar).
Backend proficiency: RESTful APIs, Node.js/TypeScript or Python, Git, and SQL databases (e.g., PostgreSQL).
Frontend familiarity: experience with React or Angular.
Practical, hands-on use of AI tools (code assistants, prompt engineering, AI-assisted debugging/testing) to boost productivity, with the judgment to validate outputs responsibly (bias, cost, ethics, accuracy).
Working understanding of core AI/LLM concepts (tokens, context length, embeddings, hallucinations) and safe vs. unsafe use cases (privacy, security, fairness).
Ability to write readable, well-tested, secure code aligned with SOLID principles.
Strong communication skills — able to discuss architectural decisions and explain technical concepts clearly.
Passion for continuous learning and curiosity about how AI is transforming software engineering.

Nice To Haves

Experience with AWS CDK, TypeScript, and React.
Microservices and event-driven architecture.
CI/CD pipelines and automated testing on AWS, including AI-assisted DevOps tooling.
Practical experience deploying and managing AI applications in production.
Understanding of MLOps challenges: prompt/flow management, data drift, performance monitoring, RAG pipelines, or semantic search.

Responsibilities

Design and implement secure, scalable, fault-tolerant, high-performing solutions using AWS serverless technology — event-driven, highly observable, and built with infrastructure as code.
Collaborate with AI researchers/engineers to translate AI and LLM capabilities into robust, production-grade services, and help other teams integrate them.
Build and maintain the pipelines needed to deploy, monitor, and manage AI services at scale — observable, resilient, and cost-effective.
Use AI-powered development tools (code assistants, test generation, architecture exploration) responsibly to accelerate delivery and improve quality, always validating outputs.
Participate in architecture discussions and design reviews, and contribute to product design by understanding customer problems — especially where AI can offer a breakthrough solution.
Work in a collaborative, agile environment: pair, plan, and execute as a team, optimizing for team productivity and healthy delivery metrics (e.g., DORA).