Why This Job is Featured on The SaaS Jobs
This Senior AI Engineer role stands out in the SaaS landscape because it targets a core product problem that is inherently multi-tenant and multi-jurisdictional: automating payroll and payments workflows across many countries. Building AI in this kind of B2B platform context typically means dealing with messy documents, evolving regulations, and high expectations for correctness, which makes applied ML more than a feature layer and closer to a product capability.
From a SaaS career perspective, the scope spans the full lifecycle of production AI, from rapid prototyping through evaluation, guardrails, and reliability work that supports real customer operations. Experience with LLM systems, retrieval, agentic patterns, and document intelligence translates well across modern SaaS categories, particularly where AI must integrate with workflows rather than operate as a standalone model.
The role is best suited to engineers who enjoy bridging research-informed experimentation with disciplined software engineering, and who are comfortable collaborating with product and domain stakeholders such as compliance. It fits someone who wants ownership of system design choices and measurable outcomes, while working on problems where data quality, edge cases, and operational risk shape technical decisions.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
Papaya Global is a rapidly growing, award-winning B2B tech unicorn with an ambitious mission to revolutionize the payroll & payments industry. With over $400M raised from multiple tier-one investors, our innovative technology provides a comprehensive solution for managing global workforces, encompassing everything from hiring and onboarding to managing and paying employees in over 160 countries.
We're building AI to tackle one of the hardest operational challenges in business: getting workforce management right across many markets, each with its own tax rules, labor laws, payment rails, and constantly shifting policies.
In this role on our AI team, you'll build and scale core AI systems that power Papaya's products. You'll work across agentic document intelligence, autonomous agents, compliance AI, and ML-powered insights, prototyping quickly, building robust evaluations, and shipping production-grade AI with real business impact.
What You'll Do
- Build and ship AI/ML solutions using LLMs, agents, RAG, and document understanding models, alongside classic ML
- Prototype quickly, validate feasibility, and turn strong POCs into production systems
- Evaluate models and architectures, apply testing and guardrails to improve agent and service reliability
- Research and apply emerging techniques: multimodal/document AI, agentic frameworks, synthetic data generation, and new architectural approaches
- Work cross-functionally with product, R&D, and compliance teams to deliver end-to-end solutions
- Contribute to scalable, secure architecture and engineering best practices for AI delivery
Requirements:
- 5+ years of experience in AI/ML engineering or applied data science with production engineering responsibilities
- Strong Python skills and solid software fundamentals
- Experience building production LLM-powered systems, including prompt design, embeddings, fine-tuning, RAG; agent experience is a plus
- Solid ML foundations; NLP, document AI, or multimodal experience is a plus
- Hands-on experience with modern AI tooling (Hugging Face, PyTorch, LangChain, LangGraph) and cloud infrastructure (AWS preferred)
- Strong communication and collaboration skills; comfortable working cross-functionally with product and domain teams
- BS/MS/PhD in Computer Science, Data Science, or Engineering (MS/PhD a plus)
