Design and build user-facing AI capabilities that simplify decision-making, surface insights, and enable faster action for operational teams.
Create and maintain multi-step LLM workflows (chains) that combine prompts, tools, and data to execute complex tasks—enabling conversational agents, data-powered assistants, and automation flows that deliver measurable process improvements.
Use retrieval-augmented generation (RAG) to combine internal data with LLMs and generate context-aware, trustworthy results.
Deliver features that set PAR apart from the competition and provide tangible value to users—leading to greater product adoption and customer retention.

5+ years’ experience as a software engineer, ideally within a SaaS or data-centric product environment
Proficiency with LLM platforms and APIs (e.g., OpenAI, Azure OpenAI)
Familiarity with prompt engineering, embedding models, and vector databases
Experience designing and implementing multi-step AI workflow chains (e.g., LangChain, Semantic Kernel, custom pipelines)
Strong data skills, including proficiency with SQL and structured datasets in production
Understanding of cloud-based orchestration tools like Azure Data Factory or equivalents
Experience taking AI features from prototype to production with attention to scalability, cost-efficiency, and observability
Strong communication skills and ability to work cross-functionally with product, engineering, and data teams
Recognized as an internal driver of AI strategy and implementation, setting standards and best practices for trustworthy, scalable AI

AI Engineer

Key skills