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 with cutting-edge digital solutions that transform industries and create measurable business impact. We're scaling globally with entities in Canada, the U.S., and India and we're looking for passionate problem-solvers who are ready to turn big ideas into real outcomes.
The Opportunity
ShyftLabs is looking for a Senior AI Engineer to sit at the intersection of AI/ML engineering and backend platform development. This isn't a research role, it's a hands-on engineering position where you'll design, build, and ship AI-powered features directly into production systems. You'll work closely with Product, Architecture, and cross-functional engineering teams to integrate intelligent capabilities into our next generation of data-driven platforms, while also contributing to the scalable backend infrastructure that powers them.
The ideal candidate combines deep AI/ML engineering experience with strong backend development skills, someone equally comfortable fine-tuning an LLM integration as they are designing a robust API or event-driven service.
Architect and implement AI-powered features end-to-end, from model integration and prompt engineering to deployment, monitoring, and iteration
Integrate LLM APIs, ML models, and intelligent automation pipelines into scalable, production-grade backend systems
Fine-tune and optimize models for performance, reliability, and cost efficiency in live environments
Design and build robust APIs, event-driven services, and third-party integrations that support AI-enabled workflows
Collaborate with Product to translate business requirements into technical AI solutions, defining scope, complexity, and dependencies
Build and maintain data pipelines and MLOps workflows to support model deployment and lifecycle management
Contribute to system architecture decisions, integration patterns, and reusable AI frameworks across the platform
Partner with data scientists and engineers to ensure smooth, scalable model deployments
Produce clear technical documentation, architecture diagrams, data flows, API specs, and AI integration patterns
Lead code reviews, enforce best practices in code quality and testing, and mentor engineers across teams
Troubleshoot complex production issues across distributed and AI-integrated systems
Stay ahead of industry trends in AI/ML tooling, frameworks, and practices
5+ years of experience building scalable, production-grade software systems
2+ years of hands-on AI/ML engineering experience, including deploying models into production environments
Bachelor's degree in Computer Science, Data Science, AI, or a related field
Strong expertise in Python, with hands-on experience using frameworks such as TensorFlow, PyTorch, or Scikit-learn
Solid backend engineering background, API development, microservices, distributed systems, and event-driven architectures
Experience integrating LLM APIs and building AI-driven features into web or platform applications
Strong proficiency in JavaScript/TypeScript and Node.js, with exposure to GraphQL
Deep experience building and consuming RESTful APIs and distributed services
Proficiency with SQL and hands-on experience with cloud platforms, GCP or AWS (e.g., S3, Lambda, RDS, EC2)
Familiarity with MLOps best practices and tools for model monitoring, versioning, and deployment
Strong understanding of software design patterns, system architecture, and data flow design
Excellent communication skills with the ability to articulate complex technical concepts clearly
Experience working in Agile/Kanban environments with a strong grasp of the full SDLC
Experience with data platforms, analytics systems, or ETL pipelines
Familiarity with real-time data processing and messaging systems such as Kafka or SQS
Exposure to tax, fintech, or compliance-related product development
Experience designing multi-tenant or enterprise-grade SaaS platforms
Background in integration-heavy environments such as ERP, financial systems, or external data providers
This Senior AI Engineer role builds and ships AI capabilities within production backend platforms. The work spans model and LLM integration, backend services, data and MLOps workflows, and collaboration with product and engineering partners.
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.
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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.
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