
AI Solutions & Development Director
- Montreal, QC
- Permanent
- Full-time
- AI Solution Architecture: Design multi-cloud reference architectures leveraging GCP, AWS, and potentially China-mainland clouds when solution sovereignty demands it
- Agentic AI & Integration: Apply agentic-LLM patterns, RAG pipelines, and architect solutions with embeddings, vector databases, MCP servers, and AI coding tools
- Security & Compliance: Embed OWASP GenAI risk mitigations and security best practices across SDLC with AI observability and strong monitoring
- Client Leadership: Lead discovery workshops, craft solution architecture, and run executive readouts for stakeholders
- Delivery: Estimate, scope and price projects; uphold delivery KPIs (security, cost, performance)
- Team Development: Build and mentor engineering teams around AI solutions and orchestrated development practices
- Coordinate across internal teams and client stakeholders across timezones
- 10+ years full-stack or platform engineering experience with 3+ years directing delivery teams
- ≥2 years hands-on GenAI: building production LLM applications, prompt engineering, integrating AI coding assistants and autonomous agent frameworks
- Multi-cloud expertise: GCP (Vertex AI) or AWS (Bedrock, Guardrails)
- Security-first approach: GenAI-specific threat modeling and guardrails implementation
- Client communication: Workshop facilitation and storytelling through documents, slides, architectural diagrams
- Technical breadth: Polyglot coding (TypeScript/Node.js, Python, Java), AI ecosystem knowledge (LangChain, LangGraph), MLOps practices
- Advanced AI experience: Fine-tuning/RLHF, modern frameworks (Vercel AI SDK, Mastra.ai)
- An understanding of the following, or comparative, technologies:
- AI Platforms: LangChain, AutoGen, CrewAI, LangGraph, PyTorch, TensorFlow, Vertex AI, AWS Bedrock, Azure OpenAI, multi-modal AI
- Data & Vector Systems: Milvus, Pinecone, Qdrant, RAG pipelines, embeddings
- Development: AI coding assistants (Cline, Roocode, Claude Code), Next.js, Nuxt.js, React Native, Flutter
- CMS & Infrastructure: Contentful, Sanity, Builder.io, Adobe AEM, Terraform, microservices
- Security: OWASP GenAI guidelines, enterprise AI security frameworks
- Cloud certifications (GCP ML Engineer, AWS ML Specialty)
- Google Professional Cloud Architect or Google Professional Cloud Developer
- Enterprise AI governance and regulatory compliance knowledge
- Work-life Balance
- Lots of opportunities for personal and professional growth
- Health Benefits Package
- Mental Health Support
- Personal Days Off
- Fertility and Menopause Leave
- Fitness Allowance
- D,E&I Initiatives
- And much more...