ShyftLabs

Data-driven decision-making platform for organizations

AI Engineer Intern

AI Application EngineeringConfirmed live in the last 24 hours

InternshipToronto, ON, CanadaCA$20 - CA$30 /hr

About the Job

Requirements

Currently pursuing or recently completed a degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.
Have strong programming skills in Python.
Have a good understanding of machine learning, natural language processing, and large language model fundamentals.
Have experience building at least one large-language-model-powered or agentic application.
Be familiar with prompt engineering, embeddings, retrieval-augmented generation, tool calling, and structured outputs.
Have experience working with APIs, Git, databases, and standard software engineering practices.
Be able to research complex technical problems and experiment with different approaches.
Have a strong interest in building reliable AI systems rather than only basic large language model demonstrations.

Responsibilities

Build and improve agent orchestration and multi-agent workflows.
Develop agentic applications for enterprise use cases using Continuum.
Work with commercial and open-source models, including OpenAI, Anthropic, Gemini, Llama, Qwen, and Mistral.
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.

Desired Qualifications

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

About ShyftLabs

At ShyftLabs, we live and breathe data. Since 2020, we’ve been helping Fortune 500 companies unlock growth through innovative digital solutions that drive real business impact. With teams across Canada, the U.S., and India, we’re growing quickly and looking for curious, motivated individuals who are excited to learn, build, and solve meaningful problems with technology.

About Continuum

Continuum is an enterprise AI agent execution and control platform designed to help teams build, run, and deploy reliable agentic applications. It provides agent orchestration, multi-model routing, persistent memory, tool integration, durable workflows, governance, guardrails, evaluation, and observability.

We are looking for an AI Engineer Intern interested in building production-ready AI agents and applications. You will contribute to the Continuum platform while also using it to build agentic applications for real enterprise use cases.

This is a hands-on engineering role. You will work across agent orchestration, memory systems, model optimization, retrieval, tools, guardrails, evaluation, and application development.

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)

Why You’ll Love Working at ShyftLabs

At ShyftLabs, your work matters. We’re a growing data product company making a big impact with Fortune 500 clients and as we scale, you’ll have the chance to shape solutions, influence strategy, and grow your career alongside us.

Here’s what you can expect when you join our team:

-Hybrid Flexibility: Enjoy a hybrid model with three days per week in our Toronto office.

-Downtown Toronto Office: Work in the heart of the city.

-Growth & Learning: Access extensive learning and development resources to keep leveling up your skills.

Inclusion at ShyftLabs

We’re building something big, and we want you on the journey with us. If you’re ready to use data and innovation to make an impact, apply today and let’s grow together.

ShyftLabs is an equal-opportunity employer committed to creating a safe, diverse, and inclusive environment. We encourage applicants of all backgrounds including ethnicity, religion, disability status, gender identity, sexual orientation, family status, age, and nationality to apply. If you require accommodation during the interview process, let us know and we’ll be happy to support you.

About the Company

ShyftLabs

Data-driven decision-making platform for organizations

ShyftLabs helps organizations adopt a data-first approach to decision making by establishing repeatable data practices and governance that turn data into timely insights. Its offering designs and implements data-driven decision workflows and analytics pipelines so teams access trustworthy data with clearly defined metrics and actions. Unlike tools that provide dashboards alone, ShyftLabs builds end-to-end processes that standardize how data is measured, analyzed, and used in decisions. Its goal is to help organizations move faster and make better choices, staying ahead of the competition.

Company size: 11-50
Company stage: Not listed
Total funding: Not listed
Headquarters: Canada
Founded: 2018

Recently Posted Jobs

Explore more opportunities at ShyftLabs

See more jobs