ShyftLabs Announces Official OpenAI Partnership
ShyftLabs
ShyftLabs announced that it became an official OpenAI partner as it expands enterprise AI solutions and production deployments.
Read articleAbout 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.
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.
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
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.
An AI Engineer Intern will help build production-oriented AI agents and applications on the Continuum platform, contributing to both platform capabilities and enterprise use cases. The work spans agent workflows, model routing, memory, retrieval, integrations, safety, evaluation, and application development.
ShyftLabs builds enterprise data and AI systems for organizations in retail, healthcare, financial services, energy, government, manufacturing and supply chain. Its work spans applied intelligence, data infrastructure and engineering, activation and analytics, and governance and security. The company also develops Continuum, an agentic AI platform comprising an open-source agent runtime, Aura for intelligent model routing, and Provenance for governance and observability. ShyftLabs says it has launched more than 50 enterprise solutions and employs more than 250 data and AI specialists across locations including Toronto, New York, Dubai and India.
ShyftLabs offers candidates exposure to enterprise AI, data engineering and agentic AI projects used by major retailers, healthcare organizations and public-sector clients. The company says it has more than 250 data and AI specialists and has launched over 50 enterprise solutions. Its Continuum platform includes an open-source agent runtime, intelligent model routing and AI governance, creating work across agents, distributed systems, data infrastructure and security. Current roles reference Python, Databricks, Spark, AWS, Azure, GCP, Terraform and Kubernetes. Job postings also highlight technical ownership, mentoring, professional development, employer-paid health benefits in Canada and hybrid flexibility for applicable roles.
Programming Language
Backend Framework
Frontend Framework
Database
Database
Data and AI Platform
Data Processing
Data Processing
Data Platform
Cloud Data Platform
Data Transformation
Data Orchestration
Cloud Infrastructure
Cloud Infrastructure
Cloud Infrastructure
Infrastructure as Code
Containers
Container Orchestration
Workflow Orchestration
Vector Database
Vector Database
AI Observability
Machine Learning Platform
Cloud Data Warehouse
Founder and CEO of ShyftLabs with a background in analytics, product and retail technology. Before founding ShyftLabs, Khandelwal worked at companies including Jet.com, Citi and Evernote and co-founded Minoan. He holds an MS in Operations Research from Columbia University and a BE in Computer Science from Panjab University.
Leads security and privacy initiatives at ShyftLabs and contributes to the company's enterprise AI governance work. His background includes software engineering, application security, penetration testing and cloud security, with prior cybersecurity experience at KPMG and professional certifications across AWS and Google Cloud.
Leads consulting and services at ShyftLabs, helping translate enterprise business requirements into data, AI and digital transformation programs. His background includes product management, consulting and entrepreneurship, including co-founding healthcare technology venture InsightHx.
ShyftLabs
ShyftLabs announced that it became an official OpenAI partner as it expands enterprise AI solutions and production deployments.
Read articleShyftLabs
ShyftLabs introduced Aura, a model-routing layer within Continuum that can route AI requests across more than 250 models and 45 providers according to quality, latency, cost and policy requirements.
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ShyftLabs disclosed its work on the data foundation supporting MAC Cosmetics' Shopify storefront, including real-time activation, consent and privacy enforcement and unified customer profiles.
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ShyftLabs hosted AgentShyft during Toronto Tech Week, where developers built production-oriented agentic AI applications using the company's Continuum framework.
Read articleShyftLabsToronto, CanadaFull time
ShyftLabsToronto, CanadaFull time
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