Company: Project X Ltd.
Location: Toronto, Ontario
Employment Type: Full Time
Location: (Hybrid working model)
Salary Range: $120,000-$160,000K CAD
Role SummaryProject X Ltd. is seeking a Staff-level, hands-on software and ML engineering professional for an embedded, client-facing engagement supporting a team that automates marketing decisions and workflows. The successful candidate will design and build production integrations between AI agents, enterprise APIs, agent orchestration frameworks and managed AI services, enabling agent-driven workflows to safely create, launch, measure and manage business activity. This role requires deep, current fluency in LLMs, agent orchestration and the Model Context Protocol (MCP), and sits between Senior and Principal level. There are no direct reports for this position.
Key Responsibilities- Design and implement production integrations between AI agents, enterprise APIs and operational systems
- Build production-grade services that let agents invoke tools and execute business actions reliably
- Connect client owned automation APIs to an agent orchestration layer and third-party managed agents
- Integrate LLM-based agents with internal and external services using APIs, MCP and related agent-tool patterns
- Contribute to agent-to-agent and agent-to-tool communication patterns
- Build for reliability: validation, error handling, retries, fallbacks, logging, observability and secure access
- Participate in architecture and system-design decisions while remaining directly responsible for implementation
What We're Looking For - Required Qualifications- 8+ years of professional software, ML or AI engineering experience
- Production experience building LLM-based applications and agentic systems, including agent orchestration and tool/function calling
- Practical experience with the Model Context Protocol (MCP), including exposing or consuming tools/resources
- Advanced Python development with strong production software-engineering practices (testing, CI/CD, Git)
- API development and integration (REST, service-oriented architectures), plus distributed systems and event-driven patterns
- Experience deploying and operationalizing machine learning models in production
- Ability to design guardrails, validation and failure-handling patterns for non-deterministic AI workflows
- Strong communication skills for an embedded, client-facing engineering environment
Nice to Have- Experience with LangChain, LangGraph or comparable agent frameworks (e.g., LangChain Deep Agents)
- Experience with multi-agent or agent-to-agent architectures and awareness of their common failure modes
- FastAPI, Docker, Kubernetes and a major cloud platform (AWS, GCP or Azure)
- Vector databases/retrieval systems and ML lifecycle tooling (MLflow, Weights & Biases or comparable)
- Slack APIs or other enterprise messaging integrations
How to Apply:Please apply with your resume and cover letter.
