10 hours ago
Toronto, CanadaSenior
Responsibilities
- Partner with enterprise clients to translate business objectives into scalable GenAI and agentic AI solutions.
- Lead technical discovery sessions, architecture workshops, solution design discussions, and stakeholder presentations.
- Design end-to-end architectures covering LLM integration, RAG, agent orchestration, data processing, APIs, and enterprise-system integration.
- Build AI agents, multi-agent systems, intelligent workflows, Python services, API integrations, and reusable AI application components.
- Process unstructured content including documents, PDFs, OCR outputs, and images for extraction, classification, retrieval, and summarization.
- Use Databricks AI capabilities and AI application frameworks to implement orchestration, state management, model serving, and tool-enabled workflows.
- Define evaluation, testing, observability, guardrail, responsible-AI, human-in-the-loop, and fallback strategies.
- Review architectures, code, and agent workflows for quality, scalability, security, maintainability, and operational readiness.
- Support production deployment, troubleshooting, optimization, and transition of AI solutions into sustainable enterprise operations.
Requirements
- 8+ years of 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 enterprise data, including PDFs, documents, OCR outputs, and images.
- Strong Python development skills, including API development, integrations, debugging, and software engineering practices.
- Experience with LangChain, LangGraph, or equivalent agent-orchestration technologies.
- Familiarity with Databricks 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 with attention to scalability, security, monitoring, and cost optimization.
- Ability to assess AI architectures, review code and agent workflows, and provide actionable technical recommendations.
- Strong communication, presentation, collaboration, and client-stakeholder engagement skills.
Benefits
- Opportunity to shape solutions and influence strategy at a growing data product company serving Fortune 500 clients.
- Equal-opportunity, diverse, and inclusive work environment with interview accommodations available upon request.
Tech Stack
Categories
Forward DeployedSolutions Engineering
About ShyftLabs
ShyftLabs builds and runs enterprise data and AI platforms, combining data engineering, analytics, and responsible AI controls with consulting and managed delivery. It designs governed data infrastructure, customer and retail analytics, and omnichannel marketing data products for large organizations. Founded in 2018 and headquartered in Toronto, the privately held firm serves global clients and staffs teams across Toronto, New York, Dubai, and New Delhi.