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AI Agentic Platform Engineer

2 weeks ago

Toronto, Ontario, Canada Vsync Solutions Full time $120,000 - $180,000 per year

Overview

Our client is building a next-generation AI Agentic Platform to accelerate enterprise adoption of autonomous AI systems across the organization. As an
AI Agentic Platform Engineer
, you will play a critical role in developing the frameworks, orchestration logic, and governance tools that enable business lines to design, deploy, and manage AI agents at scale. This is a hands-on engineering role with a focus on Python-based development, platform orchestration, integration frameworks, and security.

What You'll Do

  • Design and develop core agentic AI platform components in Python, including SDKs, frameworks, and orchestration services.
  • Build APIs and integration layers to help business lines onboard and operationalize AI agents.
  • Implement platform-level governance, observability, and lifecycle management.
  • Integrate
    MCP-Context-Forge
    for advanced context management and multi-agent workflows.
  • Ensure
    Unified Network Security & Observability for Kubernetes
    across hybrid deployments.
  • Collaborate with data scientists, AI researchers, and product teams to turn business needs into platform capabilities.
  • Embed responsible AI principles (fairness, transparency, explainability, compliance, and security) into platform services.
  • Prototype and evaluate orchestration frameworks (e.g., LangChain, Semantic Kernel, Haystack) for enterprise use.
  • Contribute to internal Python libraries and utilities that standardize AI agent development.

What You Bring

  • Advanced expertise in
    Python development
    — building frameworks, APIs, and developer platforms.
  • Hands-on experience with
    MCP-Context-Forge
    for orchestration and context management.
  • Strong understanding of
    Kubernetes network security & observability
    in enterprise settings.
  • Experience with LLM orchestration frameworks, multi-agent systems, or conversational AI pipelines.
  • Familiarity with MLOps, workflow orchestration, and model serving (custom development focus).
  • Strong foundation in enterprise software engineering (testing, packaging, versioning, CI/CD).
  • Knowledge of
    responsible AI
    and compliance requirements in regulated industries.

Nice-to-Haves

  • Experience building internal
    Python SDKs, libraries, or APIs
    for enterprise adoption.
  • Familiarity with financial services use cases (fraud detection, risk, client engagement).
  • Ability to translate abstract business requirements into modular, reusable platform components.
  • Strong collaboration skills across data science, engineering, and security teams.

Why Join

This is an opportunity to shape the future of AI in enterprise environments. You'll work with cutting-edge technologies, contribute to large-scale AI adoption, and help ensure deployed AI systems are secure, responsible, and impactful.