AI Platform Developer, Sr.

Dayforce

1d•$94,500 - $147,600•Remote

About The Position

Dayforce is a global human capital management (HCM) company headquartered in Toronto, Ontario, and Minneapolis, Minnesota, with operations across North America, Europe, Middle East, Africa (EMEA), and the Asia Pacific Japan (APJ) region. Our award-winning Cloud HCM platform offers a unified solution database and continuous calculation engine, driving efficiency, productivity and compliance for the global workforce. Our brand promise - Makes Work Life Better™ - Reflects our commitment to employees, customers, partners and communities globally. About the Opportunity Location: Work is what you do, not where you go. For this role, we are open to remote work and can hire anywhere in the United States or Canada. We are looking for an AI Platform Developer Senior to help shape the future of how developers build with AI. This role sits at the intersection of infrastructure, tooling, and developer experience, focused on building a scalable platform for developing, deploying, and maintaining AI applications. You will work within a modern cloud-based environment, enabling internal teams and external developers to leverage AI technologies to build code assistants, autonomous agents, and full-stack AI applications. If you are passionate about making AI accessible, efficient, and secure, this is an opportunity to make a lasting impact.

Requirements

Bachelor’s degree in Computer Science, Data Science, or a related field.
6+ years of software engineering experience, including 4+ years focused on AI/ML infrastructure or platform development.
Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform and their machine learning services.
Familiarity with cloud-native AI platforms such as Replit, Vercel, LangChain, or similar technologies.
Strong experience building distributed systems and scalable compute infrastructure using technologies such as Kubernetes and serverless architectures.
Solid understanding of LLMs, vector databases, RAG pipelines, and model fine-tuning workflows.
Strong programming skills in Python; experience with Go, TypeScript, or JavaScript is an asset.
Experience with MLOps platforms and practices such as MLflow, Weights & Biases, Azure ML, or Vertex AI.
Strong understanding of cloud security, observability, and performance engineering principles.
Excellent problem-solving, collaboration, and communication skills.

Nice To Haves

Direct experience integrating AI capabilities into developer platforms, IDEs, code assistants, or copilots.
Experience working with cloud-native AI development platforms such as Replit, Vercel, LangChain, or similar solutions.
Hands-on experience with LLMs, vector databases, RAG pipelines, and model fine-tuning.
Contributions to open-source AI tools, frameworks, or platforms.
Experience optimizing LLMs for low-latency inference in browser or edge computing environments.
Strong product intuition and a track record of building tools that developers love.
Passion for democratizing AI and enabling builders of all skill levels to succeed.

Responsibilities

Design and build scalable infrastructure supporting AI workloads, including inference, training, and fine-tuning within a cloud-native, multi-tenant platform.
Develop tools, APIs, and libraries that simplify the development and deployment of AI and LLM-based applications.
Integrate and optimize large language models (LLMs), retrieval-augmented generation (RAG) pipelines, vector databases, embedding stores, and multimodal systems.
Implement MLOps best practices for model versioning, deployment, monitoring, and performance optimization.
Collaborate with Engineering, Product, and Research teams to deliver AI-powered capabilities that enhance developer experiences.
Ensure platform reliability, scalability, security, and responsible AI practices.
Evaluate emerging AI tools, frameworks, and technologies for platform adoption and innovation.
Contribute to architectural decisions that support long-term platform growth and maintainability.
Drive continuous improvements in developer productivity and platform capabilities.