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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Developer, AI Experience - **Company:** Dayforce, Inc. - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $161,000.0 - $287,500.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Software Design Patterns, Software Engineering, Delivery Pipeline, Large Language Models, Ceridian Dayforce, Data Analytics, Virtual Agents - **Published:** May 19, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=25a9684aaeb6c4ca ## About the Role Do you have experience in Vendor relationship management?, * Strong software engineering background with experience delivering and operating complex production systems. * Hands-on experience using agentic coding tools and AI-assisted development workflows on real engineering problems. * Experience implementing developer workflows across repositories, testing frameworks, CI/CD pipelines, and delivery processes. * Experience with context engineering including prompts, retrieval strategies, memory/state patterns, and LLM tooling configurations. * Experience designing reusable agent skills with defined contracts, evaluation coverage, and operational safeguards. * Demonstrated ability to define engineering standards, guardrails, and evaluation frameworks that improve consistency and quality across teams. * Experience partnering directly with development teams to implement shared engineering practices. * Strong technical judgment distinguishing scalable engineering practices from experimental concepts. * Experience working across organizational boundaries to improve engineering effectiveness and implementation consistency. * Excellent written communication skills with the ability to translate emerging technical practices into actionable engineering guidance. What Would Make You Stand Out * Experience building AI engineering enablement programs at scale. * Strong understanding of LLM evaluation methodologies and operational reliability patterns. * Experience designing enterprise AI developer platforms or reusable internal tooling ecosystems. * Demonstrated ability to influence engineering standards and adoption across large organizations. * Strong understanding of balancing experimentation, governance, scalability, and developer productivity in AI-assisted engineering environments. ## Description Dayforce is building an AI Developer Experience team within Engineering to scale high-quality, agentic development practices across the organization. This team transforms early-stage experimentation into durable, reusable engineering capabilities that development teams can adopt in real codebases under real delivery pressure. The Staff Developer, AI Experience is a senior hands-on engineering role and a key contributor to the broader AI Engineering strategy. This role focuses on building the systems, standards, workflows, and reusable development capabilities that enable engineers to work more effectively with AI-assisted and agentic coding tools. The role combines architectural thinking with hands-on implementation, helping define scalable engineering patterns while working directly within repositories and delivery environments to operationalize modern AI-driven development practices. What You'll Get to Do * Own and evolve reusable skill design patterns and coding artifact standards that drive AI-assisted development effectiveness across Engineering. * Define how agent context is structured, scoped, and maintained across repositories, toolchains, and delivery pipelines. * Design reusable context patterns including prompts, retrieval strategies, memory/state patterns, and tool exposure configurations. * Establish practical guardrails and standards that reduce failure modes and support responsible AI-assisted development adoption. * Build and maintain reusable AI agent skills, workflows, templates, scaffolding, and implementation guides. * Define production-readiness standards for reusable skills including contracts, triggers, evaluation coverage, failure handling, and documentation. * Partner directly with development teams to operationalize AI-assisted workflows in repositories, testing practices, and engineering delivery processes. * Establish standards for emerging engineering artifacts such as AI-assisted specifications, implementation plans, and workflow patterns. * Define evaluation and adoption criteria for scalable AI engineering capabilities including reliability, engineering value, and maintainability. * Build data-driven visibility into AI-assisted development outcomes and ROI across Engineering. * Define scalable implementation standards that support consistent and lightweight AI engineering adoption. * Partner with internal platform teams and external vendors on tooling integration, feedback, and capability evolution. * Help establish and evolve the AI Engineering enablement operating model including priorities, success metrics, and organizational scaling strategies. ## Related Videos - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [AI in Leadership: How Technology is Reshaping Executive Roles](https://www.wearedevelopers.com/videos/1705-ai-in-leadership-how-technology-is-reshaping-executive-roles) - [How will artificial intelligence change the future of software testing?](https://www.wearedevelopers.com/videos/85-how-will-artificial-intelligence-change-the-future-of-software-testing) - [Hiring AI Native Talents](https://www.wearedevelopers.com/videos/100268-hiring-ai-native-talents) - [How Data is Shaping our Games](https://www.wearedevelopers.com/videos/176-how-data-is-shaping-our-games) - [AI Killed DevOps... 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