Senior Backend Engineer
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- Canada
- Permanent
- Temps-plein
- Design and implement feature modules end-to-end: DTOs, controllers, services, and providers following established module patterns across domain areas including authentication, user management, AI integration, file handling, and conversation threading
- Enforce JWT authentication guards, integrate Azure Cosmos DB using parameterized queries (never interpolated), and instrument all contributions with OpenTelemetry distributed tracing
- Author and maintain Swagger/OpenAPI documentation for every new and modified endpoint - API contracts are first-class deliverables
- Apply structured OgmaLogger logging consistently across all contributions; structured observability is a non-negotiable part of every feature
- Write unit tests and e2e tests as part of delivery - mock Cosmos DB and external dependencies, maintain meaningful coverage without being directed to do so
- Contribute production-ready route handlers, Pydantic models, and async service logic to the RAG orchestration service and the doc-parser-api document processing pipeline
- Implement and extend Azure AI Search integrations, embedding pipelines, and document ingestion workflows - batch embedding operations, OCR fallback paths, and multi-format document processors
- Execute quality gates on all Python contributions: ruff linting, mypy static type checking, pytest with a minimum 80% coverage threshold, and bandit security scanning
- Participate in code reviews across all repositories; provide substantive, reasoned technical feedback and uphold Conventional Commits and Semantic Versioning standards
- Leverage agentic coding tools - Claude Code, GitHub Copilot, and their successors - as daily productivity multipliers within a disciplined engineering workflow
- Collaborate with AI/ML engineers, frontend engineers, and product managers to translate complex AI capabilities into reliable, observable, production-ready backend services
- Contribute to backend architectural decisions: module design, API contract conventions, Azure service integration patterns, CI/CD pipeline configuration, and cross-service dependency management
- 5-7 years of professional backend engineering experience delivering production services at meaningful scale
- TypeScript - rigorous typing discipline in a Node.js backend context; you think in types and leverage the type of system rather than work around it
- NestJS or equivalent Node.js backend framework (Express, Fastify) - experience designing feature modules, middleware, guards, interceptors, and RESTful API architecture
- Python - comfortable authoring production-grade services with Pydantic data models and async/await patterns; you write clean Python and know when something is good enough versus when it needs to be better
- Azure ecosystem - practical experience with managed identity (DefaultAzureCredential), Key Vault, Cosmos DB, Blob Storage, and Application Insights; secrets are never hardcoded
- Testing discipline - writes unit, integration, and e2e tests as an intrinsic part of delivery, not a post-hoc checkbox; knows the difference between a test that proves correctness and one that just passes
- Observability fundamentals - structured logging, distributed tracing, and error tracking in a cloud-hosted service; you know what to instrument and why
- Git workflow fluency - feature branching, pull request workflows, code review participation, and CI/CD integration; you leave the codebase in a better state than you found it
- Proven delivery track record - demonstrable history of shipping features into production environments on schedule, sprint over sprint
- Azure AI Search, Azure OpenAI, or RAG architecture - hands-on experience with vector search, embedding pipelines, or LLM integrations in production
- OpenTelemetry instrumentation - distributed tracing across polyglot service boundaries, especially Python and Node.js in the same trace
- Agentic coding assistants - Claude Code, GitHub Copilot, or equivalent tools used as a genuine workflow accelerant; you know how to direct an agent, review its output critically, and integrate it into a disciplined engineering process
- Document processing pipelines - OCR, PDF/DOCX parsing, text chunking strategies, or file ingestion workflows at scale
- Regulated industry exposure - insurance, financial services, or healthcare environments where data privacy, auditability, and compliance shape engineering decisions
- Angular or React familiarity - enough to read frontend code, understand API consumption patterns, and collaborate on contract design without handholding from the UI team
- Open-source contributions - anything that demonstrates you care about the craft beyond the job