For over four decades, PAR Technology Corporation (NYSE: PAR) has been a leader in restaurant technology, empowering brands worldwide to create lasting connections with their guests. Our innovative solutions and commitment to excellence provide comprehensive software and hardware that enable seamless experiences and drive growth for over 100,000 restaurants in more than 110 countries. Embracing our "Better Together" ethos, we offer Unified Customer Experience solutions, combining point-of-sale, digital ordering, loyalty and back-office software solutions as well as industry-leading hardware and drive-thru offerings. To learn more, visit partech.com or connect with us on LinkedIn, X (formerly Twitter), Facebook, and Instagram.
Position Description:
We are seeking a pioneering AI Engineer to be the first dedicated AI specialist in the PAR Retail R&D organization. This is a hands-on builder role focused on architecting and integrating our first generation of AI-powered products and services. You will turn business needs into production-ready solutions by leveraging a strong foundation in machine learning alongside modern Generative AI, including agentic workflows that use tools, retrieval, and orchestration to complete real tasks. As our go-to expert, you will define the foundational architecture for integrating modern AI platforms, establish engineering best practices, and drive an experimentation and evaluation mindset to ship reliable solutions.
Position Location:
Reports To:
What We’re Looking For:
Proven experience building multi-agent systems, orchestrators (planning, task routing, tool calling, state/memory, approvals, retries, and safe fallbacks) and MCP endpoints.
Hands-on experience with agent frameworks and orchestration tooling (e.g., LangGraph, LangChain, LlamaIndex, CrewAI, n8n, or equivalent).
Evaluation-first mindset for agents: test sets, scoring thresholds, regression gates, and quality monitoring over time.
Proven experience architecting solutions using modern AI services from major cloud providers (e.g., Azure OpenAI, Amazon Bedrock, Google Vertex AI).
Responsible AI experience focused on privacy, security, access control, and defenses against prompt injection and tool misuse.
Additional skills:
Experience with advanced approaches beyond LLM apps (e.g., deep learning, classical ML, reinforcement learning) is a plus.
Experience building and operating agentic systems in production: observability (tracing/metrics/logs), CI/CD, and incident-ready monitoring (e.g., DataDog, Grafana).
Experience defining and tracking success metrics for agent workflows (task completion rate, quality scores, latency, cost, escalation rate) plus business KPIs.
Unleash your potential: What you will be doing and owning:
Architectural Strategy: Define and establish the foundational architecture and best practices for AI systems across PAR, ensuring solutions are scalable, maintainable, secure, and robust from the ground up.
Zero-to-One Building: Take ambiguous problems from concept to production, building core components and workflows from scratch, iterating quickly through prototypes, and hardening into reliable, repeatable systems.
End-to-End Agentic AI Implementation: Design, build, and operate agentic solutions and workflow automations that go beyond chat, including multi-agent orchestration, MCPs, tool calling, retrieval-grounded reasoning, state/memory, approvals, retries, and safe fallbacks, through production monitoring.
Proof-of-Concept Refinement: Collaborate with other engineers to evaluate existing PoCs. Identify areas for improvement, tighten reliability and quality, and re-architect solutions for scalability, performance, and cost.
AI Ops & Infrastructure (LLMOps/AgentOps): Establish and champion production practices for agentic systems, including prompt/version control, evaluation pipelines, tracing/observability, automated testing, release gates, and cost/latency controls.
Strategic Collaboration: Work closely with product managers, data analysts, and business leaders to identify high-impact opportunities for AI. Translate requirements into technical specifications and actionable project plans.
Interview Process:
Interview #1: Video Screen with Talent Acquisition Team (via MS Teams)
Interview #2: Video interview with a cross functional partner (via MS Teams)
Interview #3: Video interview with hiring manager (via MS Teams)
Take-home/technical exercise
Interview #4: Technical Interview/Exercise review with a panel (via MS Teams)
PAR is proud to provide equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. We also provide reasonable accommodations to individuals with disabilities in accordance with applicable laws. If you require reasonable accommodation to complete a job application, pre-employment testing, a job interview or to otherwise participate in the hiring process, or for your role at PAR, please contact accommodations@partech.com. If you’d like more information about your EEO rights as an applicant, please visit the US Department of Labor's website.
