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)