Forward Deployed AI Solutions Architect (GenAI & Agentic AI)
New
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ShyftLabsArtificial intelligence
Workplace type: Remote; Listing location: Toronto, OntarioFull-TimeSenior
Salary160,000 - 190,000 CAD per year
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Job Details
- Experience
- 8+ years of overall experience in software engineering, solution architecture, AI/ML engineering, or related technical roles; at least 2 years of hands-on experience developing Generative AI applications and LLM-powered solutions.
- Required Skills
- PythonMLFlowLLMGenerative AILangChain
Requirements
- 8+ years of overall experience in software engineering, solution architecture, AI/ML engineering, or related technical roles.
- At least 2 years of hands-on experience developing Generative AI applications and LLM-powered solutions.
- Demonstrated experience designing and building AI agents, agentic workflows, and multi-agent applications.
- Strong practical knowledge of LLMs, RAG architectures, embeddings, vector databases or vector search, prompt engineering, and tool/function calling.
- Experience processing unstructured data, including PDFs, documents, OCR outputs, and images.
- Strong Python development skills, including API development, integration patterns, debugging, and software engineering best practices.
- Experience with AI application frameworks such as LangChain, LangGraph, or equivalent agent orchestration technologies.
- Familiarity with Databricks AI capabilities, including AI Functions, AI Search/Vector Search, Model Serving, and MLflow.
- Experience with AI evaluation frameworks, hallucination testing, guardrails, human-in-the-loop patterns, and AI observability.
- Experience deploying AI applications into production, including scalability, security, monitoring, and cost optimization.
- Ability to assess AI architecture proposals, review code and agent workflows, and provide actionable technical recommendations.
- Strong communication and presentation skills for explaining technical concepts, trade-offs, and recommendations to enterprise clients.
Responsibilities
- Partner with enterprise clients to understand business objectives, identify AI opportunities, and translate requirements into scalable GenAI and agentic AI solutions.
- Lead technical discovery sessions, architecture workshops, and solution design discussions with client stakeholders and cross-functional teams.
- Design end-to-end AI architectures covering LLM integration, RAG, agent orchestration, data processing, APIs, and enterprise system integration.
- Develop solution blueprints, technical specifications, architecture diagrams, and implementation roadmaps.
- Design and build enterprise GenAI applications using LLMs, embeddings, vector search, prompt engineering, and tool/function calling.
- Architect and implement AI agents, multi-agent systems, and agentic workflows for complex business processes.
- Develop Python services and API integrations, and build workflows connecting LLMs with enterprise data, applications, and external tools.
- Establish evaluation, guardrail, human-in-the-loop, testing, and observability practices for AI solutions.
- Support production deployment, troubleshooting, and continuous improvement of AI solutions.
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