13 days ago
Base Salary
$116k - $181k/yr
Responsibilities
- Partner with analytics and business stakeholders to translate decisions, workflows, and pain points into technical requirements and AI solution designs.
- Build conversational analytics experiences, AI assistants, agents, and decision-support workflows over governed enterprise data.
- Deliver AI use cases from discovery and prototyping through user validation, production deployment, monitoring, and ongoing improvement.
- Implement retrieval-augmented generation, tool calling, vector or semantic retrieval, and secure integrations with enterprise services and data platforms.
- Use semantic models, metrics, metadata, business definitions, lineage, and authorized enterprise data to ground and trace AI responses.
- Develop automated tests and evaluation scenarios and monitor response quality, accuracy, relevance, latency, cost, failures, feedback, and adoption.
- Apply enterprise security, privacy, identity, authorization, data governance, and Responsible AI requirements throughout solution delivery.
- Collaborate with Enterprise AI Platform, Data Engineering, Architecture, Security, Privacy, Legal, and Data Governance teams and document reusable implementation patterns.
Requirements
- Typically 5 or more years of related experience with a bachelor's degree, 3 or more years with a master's degree, or equivalent practical experience in software, data, analytics, AI, ML engineering, or data science.
- Hands-on experience building and deploying production data, analytics, AI, or generative AI solutions.
- Strong Python, SQL, and software engineering skills, including experience with APIs, testing, version control, and CI/CD practices.
- Working knowledge of LLMs, retrieval-augmented generation, AI agents, tool calling, embeddings, vector search, semantic retrieval, and enterprise knowledge integration.
- Experience with enterprise AI services or platforms such as Azure AI Foundry, Azure OpenAI, OpenAI, Anthropic, or comparable technologies.
- Experience with analytical data platforms, warehouses or lakehouses, semantic models, APIs, and BI technologies such as Microsoft Fabric, Power BI, Databricks, or Snowflake.
- Understanding of semantic and dimensional modeling, business metrics, metadata, data quality, lineage, and governed data access.
- Experience applying authentication, authorization, RBAC, identity propagation, and secure access practices to AI or data solutions.
- Understanding of LLMOps or MLOps concepts, including deployment, evaluation, monitoring, observability, and production support.
- Ability to work independently through diverse technical problems and communicate effectively with senior business and technical stakeholders.
- Preferred experience taking AI or analytics solutions from business discovery through prototype, user testing, production deployment, and adoption, especially conversational analytics over governed enterprise data.
Benefits
- Remote, full-time employment.
- Medical, dental, vision, and life insurance.
- 401(k) plan with company match.
- Unlimited time away from work, 10 paid US holidays, up to 80 hours of paid sick time, and 17 weeks of paid parental leave, subject to applicable policies.
- Volunteer days, community impact opportunities, and the Dayforce Cares charity program.
About Ceridian
Ceridian, now operating as Dayforce, builds a cloud human capital management platform that unifies HR, payroll, talent, and workforce management for employers. It sells its software as a subscription and serves customers globally. Headquartered in Minneapolis, Minnesota (with a major presence in Toronto), the company traces the Dayforce brand to 2009 and is publicly traded on the NYSE after rebranding in 2024.