Senior Software Engineer – Data Platform

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Dayforce

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

👥 HR Tech

☁️ SaaS

🤝 B2B

💰 $1G Post-IPO Debt - Dayforce on 2024-03

HR Tech • SaaS • B2B

Dayforce is a cloud-based human capital management (HCM) platform offered by Ceridian that provides employers with integrated HR, payroll, benefits, workforce management (time and attendance), and talent management capabilities. It is designed as a single application to help organizations manage employee life-cycle processes, payroll and compliance, and workforce scheduling in a unified system.

📋 Description

• Design and implement API gateways, model routing layers, and service infrastructure that connect fine-tuned CRE models with production applications. • Develop internal developer tooling - prompt management interfaces, evaluation dashboards, trace viewers - that accelerate the team's ability to ship and iterate on AI features. • Implement integration patterns for embedding AI capabilities into LightBox's existing workflow applications, ensuring seamless user experiences. • Build observability and monitoring infrastructure for AI workloads: latency tracking, quality metrics, cost attribution, and usage analytics. • Contribute to the platform's knowledge retrieval and caching layers, optimizing for both accuracy and performance at scale. • Collaborate with ML engineers on model serving infrastructure, helping bridge the gap between training outputs and production deployment. • Participate in architecture decisions and technical design reviews, bringing a pragmatic full-stack perspective to the team's work.

🎯 Requirements

• 6+ years of software engineering experience with a strong full-stack foundation (backend-leaning preferred). • Production experience building APIs, microservices, and platform infrastructure in Python and/or TypeScript/Node.js. • Solid understanding of cloud infrastructure (AWS or GCP), containerization (Docker, Kubernetes), and CI/CD pipelines. • Experience building developer-facing tools, SDKs, or internal platforms that other engineers consume. • Familiarity with LLM integration patterns: API-based model consumption, prompt engineering, retrieval-augmented generation, and tool/function calling. • Strong fundamentals in distributed systems, data modeling, and API design. • Comfort working in a small team with high autonomy - you can own a feature end-to-end from design through deployment and monitoring.