Overview
Skills
Job Details
Role - GenAI
Working Location: Toronto, Hybrid - 3 days a week
Long Term
JD :
| Role Overview:We are seeking intermediate Software Engineers who can contribute across services, APIs, and Azure cloud components. Build critical services such as data ingestion, vector indexing, retrieval APIs, inference orchestration, and human validation workflows.Work closely with an Engineering Lead, AI Engineers, and QA as a part of an iterative delivery model. | ||
| Key Responsibilities: Seems FSD skills Backend & Cloud Services - Build microservices for: SharePoint delta ingestion (Graph API) Data normalization and Blob ingestion Embedding and vector indexing via Azure OpenAI + Cognitive Search Retrieval and scoring pipelines (hybrid vector + keyword search) RAG-based inference orchestration Feedback ingestion services (SQL, EventHub, Service Bus) Implement APIs using Python / NodeJS (project-lead preference will define the final stack) Implement secure access via Azure AD, Managed Identities and Key Vault Integrate parallel search workflow (existing partial search) with new AI inference pipelines | Data Engineering: Seems Data Engineer skills Build and enhance pipelines using: Azure Functions Azure Data Factory Azure EventHub / ServiceBus Create schemas and objects for the feedback loop database (Azure SQL) Ensure proper handling of PII, masking and secure data retention policies | DevOps & Testing: Seems DevOps skills Contribute to IaC deployments (Terraform) Write Unit / Integration tests Participate in performance tuning and load testing for inference services Support CI/CD pipelines using Azure DevOps |
| Documentation & Architecture Help maintain the C4 diagrams, API contracts, sequence diagrams, and operational run books |
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| Required Skills: Technical: Seems more FSD skills 4+ years of experience building backend services (Python preferred, NodeJS / Java / .NET accepted) Hands-on development with Rest APIs, server less functions, microservices, AI based development like LLM, Semantic searches, Vectors, RAG, MCP, Orchestration using Lang smith or similar Practical experience with Azure (Functions, storage, Key Vaults, Cognitive Services, Azure Foundry etc.,) Strong understanding of scalable and distributed systems, async workflows, event-based services etc., Experience with databases Familiarity with search and indexing systems (Cognitive Search, Elastic Search etc.) Good understanding of authentication (OAuth2, Machine to Machine tokens, Azure AD etc.) and secure coding practices Experience needed with Azure OpenAI, LangChain, Vector Storage, Embedding pipelines Familiarity with RAG Architectures Nice to have: Experience with SharePoint Graph API, Web-hooks etc. Prior experience in ML operations (Azure ML, pipelines etc.,) is a Plus |