AI Engineer Intern

What You'll Be Doing

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

What We Are Looking For

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

Nice to Have

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

Hourly Pay

$20 - $30/Hr (CAD)