Artificial Intelligence Engineer

Job summary

Design, build, and deploy secure production AI applications and agentic systems, including APIs, microservices, knowledge graphs, and document-rendering workflows. Integrate Azure and enterprise services while implementing AI evaluation, orchestration, observability, governance, and production delivery practices.

Job details

Position Overview VStream Labs Inc. is seeking a hands-on AI Engineer – Agentic AI to design and deliver secure, production-ready AI applications, APIs, microservices, knowledge-graph capabilities, document-rendering workflows, and intelligent agentic systems. This remote contract requires strong software engineering, Azure integration, JVM and Python experience, AI evaluation, orchestration, governance, and production delivery. Key Responsibilities • Design, build, and deploy agentic AI solutions using LLMs, retrieval-augmented generation (RAG), memory, reasoning, prompt engineering, and human-in-the-loop patterns. • Build backend services, REST APIs, and microservices using Node.js, Python, and JVM-based technologies. • Develop and integrate knowledge graphs, entity and relationship models, graph-based retrieval, and GraphRAG capabilities. • Build reliable document-generation and rendering pipelines, including HTML-to-PDF and comparable business-document transformations. • Deploy and operate solutions using Azure App Service, Blob Storage, Key Vault, API Management, Entra ID, Azure OpenAI, and related cloud services. • Implement OAuth 2.0 and OpenID Connect authentication and authorization. • Integrate ServiceNow, Jira, Microsoft Graph, and other enterprise APIs. • Evaluate AI systems using appropriate metrics and validation techniques; identify hallucinations, safety concerns, grounding issues, and model-performance risks. • Implement workflow orchestration, observability, model monitoring, GitHub Actions, CI/CD, MLOps/LLMOps, and infrastructure as code. • Apply secure engineering, responsible AI, governance, testing, and production-readiness practices. What You Need to Have to Be Considered • 8+ years of experience in AI/ML, Data Science, or Software Engineering. • Strong understanding of machine-learning algorithms, evaluation metrics, and model-validation techniques. • Expertise in Agentic AI concepts, including LLMs, RAG, memory, reasoning, and prompt engineering. • Hands-on experience building AI solutions using OpenAI, Azure OpenAI, Anthropic, Gemini, or similar platforms. • Strong Python experience and practical experience with LangChain, LangGraph, Semantic Kernel, LlamaIndex, or comparable frameworks. • Hands-on experience with the JVM ecosystem and integrating JVM-based applications or services. • Strong Node.js development, REST API, and microservices experience. • Experience with Azure App Service, Blob Storage, Key Vault, API Management, and Entra ID. • Experience implementing knowledge graphs, graph data models, graph-based retrieval, or GraphRAG. • Experience implementing production document-rendering solutions, including HTML-to-PDF or comparable document-generation pipelines. • Proven experience evaluating AI systems, detecting hallucinations, and measuring model performance. • Knowledge of scalable architecture, workflow orchestration, AI governance, and secure enterprise integration. • Experience deploying production AI solutions using MLOps/LLMOps practices. • Experience with GitHub Actions, CI/CD, and Git branching strategies. These Will Help You Stand Out • Experience with multi-agent systems and advanced orchestration frameworks. • Cloud expertise in Azure, AWS, or Google Cloud. • Knowledge of AI security, compliance, and responsible AI practices. • Experience in regulated industries such as healthcare, insurance, or banking. • Infrastructure-as-code experience. • Relevant AI, ML, or cloud certifications. Work Arrangement • Contract • Remote within Canada • Compensation range: CAD $50–$55 per hour + HST • Occasional collaboration during standard Canadian business hours may be required.

What you’ll do

Design, build, and deploy secure production AI applications and agentic systems, including APIs, microservices, knowledge graphs, and document-rendering workflows. Integrate Azure and enterprise services while implementing AI evaluation, orchestration, observability, governance, and production delivery practices.

Requirements

Requires 8+ years of experience in AI/ML, data science, or software engineering, with strong machine-learning evaluation and production AI experience. Candidates need hands-on expertise in agentic AI, Python, JVM technologies, Node.js, Azure, knowledge graphs, document rendering, and MLOps/LLMOps.

Listed skills

• Microsoft Azure · Preferred
• Node.js · Preferred
• REST APIs · Preferred
• CI/CD · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Agentic AI
• Large Language Models
• Retrieval-Augmented Generation
• Python
• Node.js
• JVM Technologies
• Azure
• Knowledge Graphs
• GraphRAG
• REST APIs
• Microservices
• AI Evaluation
• LangChain
• CI/CD
• MLOps/LLMOps
• OAuth 2.0

Job areas

• Technology
• Software
• Data & Analytics
• Engineering

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