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DailyPay is the leader in On-Demand Pay, serving over 1,900 employers and 6 million employees. As an AI Solutions Engineer, you will be embedded within DailyPay's Engineering organization, acting as the premier technical leader for integrating AI into company processes and workflows.
You will work cross-functionally with domain experts across departments to discover workflow bottlenecks, design AI-powered solutions, and build custom software, scripts, and model integrations. Your role bridges enterprise-grade AI engineering with business unit execution, ensuring technology directly translates to enhanced financial wellness for users.
Key responsibilities include:
- Shadowing domain experts to uncover workflows and pain points, then designing and shipping automation solutions (MVPs, custom scripts, API integrations) that mature into managed, durable agents
- Defining metrics with stakeholders, tracking adoption and ROI, and prioritizing projects based on feasibility, risk, and business value
- Designing, building, evaluating, and operating AI workflows with evaluation frameworks, guardrails, observability, and feedback loops
- Serving as the on-the-ground authority for AI questions, helping non-technical teams evaluate and configure AI features in their existing SaaS stack
- Mentoring peers in AI development, building reusable documentation and training, and demonstrating emerging AI capabilities across the company
- Steering hosted and local harness development with distilled problems, prototypes, and workflows from various departments
- Benchmarking model performance, optimizing prompt/token usage, managing API latency, and monitoring operational costs
- Ensuring department-level AI work adheres to company policy on data privacy, security, and ethical use
Requirements:
- 3+ years of professional software development experience with strong proficiency in Go or JavaScript (ideally both) and standard engineering practices (version control, testing)
- Hands-on experience building or contributing to applications with Large Language Models (LLMs) or managing complex workflows using AI tools; deep understanding of agent design, skills, context, and memory
- Experience working with APIs and MCPs of typical company platforms like Jira, GitHub, or Salesforce
- Exceptional ability to translate complex machine learning and engineering concepts into plain, business-friendly language for non-technical stakeholders
- Proven track record of analyzing business operations, formulating technical requirements from vague problems, and prioritizing solutions based on ROI
- High emotional intelligence with demonstrated comfort working autonomously inside non-technical departments, building trust as a collaborative peer
