AI Engineer Intern

What You'll Be Doing

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• Build and improve agent orchestration and multi-agent workflows.
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• Develop agentic applications for enterprise use cases using Continuum.
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• Work with different commercial and open-source models, including OpenAI, Anthropic, Gemini, Llama, Qwen, Mistral, and others.
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• Improve intelligent model routing based on task complexity, quality, latency, and cost.
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• Build persistent memory and state-management capabilities for long-running agent workflows.
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• Develop tool-calling functionality and integrations with APIs, databases, and enterprise systems.
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• Work with MCP servers and function tools to connect agents with external services.
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• Design context-engineering and retrieval pipelines using vector and graph databases.
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• Implement AI guardrails for safety, security, access control, data privacy, and policy enforcement.
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• Create evaluation pipelines to measure accuracy, groundedness, hallucination, tool usage, workflow completion, latency, and cost.
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• Improve the observability and traceability of agent decisions, tool calls, and workflow execution.
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• Optimize prompts, model usage, token consumption, response time, and infrastructure costs.
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• Build APIs, backend services, and user-facing prototypes for agentic applications.
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• Write clean, reusable, well-tested, and documented Python code.
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• Contribute to Continuum’s open-source codebase, examples, documentation, and developer experience.

What We Are Looking For

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• Currently pursuing or recently completed a degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.
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• Strong programming skills in Python.
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• Good understanding of machine learning, natural language processing, and LLM fundamentals.
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• Experience building at least one LLM-powered or agentic application.
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• Familiarity with prompt engineering, embeddings, RAG, tool calling, and structured outputs.
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• Experience working with APIs, Git, databases, and standard software engineering practices.
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• Ability to research complex technical problems, experiment with different approaches, and clearly communicate results.
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• Strong interest in building reliable AI systems, not just basic LLM demos

Nice to Have

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• Experience with agent frameworks such as LangGraph, LangChain, LlamaIndex, AutoGen, CrewAI, or similar technologies.
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• Familiarity with OpenAI, Anthropic, Gemini, AWS Bedrock, or open-source models.
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• Experience with vector databases such as Milvus, Pinecone, Weaviate, or Chroma.
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• Experience with graph databases such as Neo4j.
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• Knowledge of PostgreSQL, Redis, Docker, Kubernetes, or cloud infrastructure.
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• Familiarity with AI observability and evaluation tools such as Langfuse.
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• Understanding of multi-tenancy, identity management, authorization, or enterprise security.
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• Experience with model routing, inference optimization, prompt compression, or cost optimization.
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• Contributions to open-source AI projects, research, hackathons, or technically strong personal projects.

Hourly Pay

• $20 - $30/Hr (CAD)