The AI Architect will design enterprise-grade AI solutions using Generative AI, LLMs, and orchestration frameworks, focusing on building scalable systems and developing production-ready applications.
This is a remote position.
We are seeking a highly experienced AI Architect with deep expertise in Generative AI, Large Language Models (LLMs), and modern AI orchestration frameworks such as LangChain and LangGraph. The ideal candidate will have strong hands-on experience designing enterprise-grade AI solutions, building scalable RAG (Retrieval-Augmented Generation) pipelines, integrating MCP servers using Python, and developing production-ready AI applications leveraging modern LLM ecosystems.
Requirements
- 12–15+ years of overall IT experience with strong architecture background.
- Extensive hands-on experience with Python development.
- Strong expertise in LangChain and LangGraph frameworks.
- Experience integrating MCP servers using Python.
- Deep understanding of RAG architecture and LLM application development.
- Hands-on experience with vector databases such as Pinecone, Weaviate, ChromaDB, or FAISS.
- Experience working with OpenAI, Anthropic, Gemini, Llama, or other LLM ecosystems.
- Strong understanding of prompt engineering and AI orchestration patterns.
- Experience developing REST APIs and microservices.
- Familiarity with Docker, Kubernetes, and cloud platforms such as AWS, Azure, or GCP.
- Experience with AI monitoring, evaluation, and optimization techniques.
- Strong knowledge of scalable distributed systems and enterprise architecture.
Similar Jobs
Cloud • Security • Software • Cybersecurity • Automation
The Principal Solutions Architect will lead technical architectures, drive AI-focused solutions, collaborate across teams, and mentor others to guide customers in maximizing GitLab’s DevSecOps platform's value.
Top Skills:
AICi/CdCloud ComputingDevsecopsGitlab
Information Technology • Software
Design and lead enterprise Azure AI and data platforms. Create architecture diagrams, reference architectures, and implementation roadmaps; guide engineering teams; review code, pipelines, infrastructure, and deployments; translate business requirements into cloud-native AI and data solutions; evaluate technologies and communicate with technical and non-technical stakeholders.
Top Skills:
AutogenAzure Ai FoundryAzure Ai SearchAzure Api ManagementAzure Container AppsAzure Data FactoryAzure Key VaultAzure Kubernetes ServiceAzure NetworkingAzure OpenaiDnsDocument IntelligenceFabric Data FactoryFabric LakehouseFirewallFoundry AgentsManaged IdentitiesMedallion ArchitectureMicrosoft Agent FrameworkAzureMicrosoft FabricOnelakePower BIPrivate EndpointsPrompt EngineeringRbacRetrieval-Augmented GenerationSemantic KernelVnet
Retail
Senior individual contributor who architects, prototypes, and ships production-grade AI solutions for Finance. Focus areas include agentic AI, multi-agent orchestration, ML forecasting and anomaly detection, RAG and vector-store solutions, responsible AI and governance, and embedding AI into FP&A processes. Partners with engineering, IT, security, and finance teams to productionize systems and establish standards, monitoring, and controls.
Top Skills:
Agent FrameworksAPIsAWSAzureBiCi/CdData WarehouseEpm/CpmErpFoundation ModelsGCPLlm ApisOrchestration ToolsProphetPythonPyTorchRagScikit-LearnStatsmodelsTensorFlowTestingVector StoresVersion Control
What you need to know about the Montreal Tech Scene
With roots dating back to 1642, Montreal is often recognized for its French-inspired architecture and cobblestone streets lined with traditional shops and cafés. But what truly sets the city apart is how it blends its rich tradition with a modern edge, reflected in its evolving skyline and fast-growing tech industry. According to economic promotion agency Montréal International, the city ranks among the top in North America to invest in artificial intelligence, making it le spot idéal for job seekers who want the best of both worlds.
Key Facts About Montreal Tech
- Number of Tech Workers: 255,000+ (2024, Tourisme Montréal)
- Major Tech Employers: SAP, Google, Microsoft, Cisco
- Key Industries: Artificial intelligence, machine learning, cybersecurity, cloud computing, web development
- Funding Landscape: $1.47 billion in venture capital funding in 2024 (BetaKit)
- Notable Investors: CIBC Innovation Banking, BDC Capital, Investissement Québec, Fonds de solidarité FTQ
- Research Centers and Universities: McGill University, Université de Montréal, Concordia University, Mila Quebec, ÉTS Montréal
