Staff AI Engineer positions focus on delivering results in their domain. This page aggregates open Staff AI Engineer roles and what employers typically expect.
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 http://partech.com or connect with us on [LinkedIn](https://www.linkedin.com/company/partechnology/), [X (formerly Twitter)](https://twitter.com/par_tech), [Facebook](https://www.facebook.com/parpointofsale/), and [Instagram](https://www.instagram.com/partechnology/). **About the Role** PAR is looking for a **Senior /Staff AI Platform Engineer** to build and scale our next-generation AI Platform that enables engineering teams to rapidly develop, deploy, and operate **AI agents, agentic workflows, and GenAI-powered applications** across PAR's restaurant technology products. This role is ideal for an ML engineer enthusiast who knows both **Python and .NET Platform,** who is passionate about cloud-native architecture, distributed systems, developer platforms, and Generative AI. You will help build reusable AI services, orchestration frameworks, SDKs, and platform capabilities that power enterprise-grade AI solutions. **Key Responsibilities** - Design and build scalable AI platform services, APIs, SDKs, and microservices using markdown and Python supporting a **.NET** codebase. - Develop **Agentic AI capabilities**, including multi-agent orchestration, agent lifecycle management, tool integration (MCP), memory, planning, reasoning, and workflow automation. - Build production-grade **RAG pipelines**, knowledge retrieval services, vector search, and semantic search capabilities. - Develop secure, multi-tenant AI platform services with governance, guardrails, content safety, and policy enforcement. - Build real-time streaming APIs, AI evaluation pipelines, observability, monitoring, and cost optimization for AI workloads. - Collaborate with Product, Engineering, and DevOps teams to build reusable AI capabilities and accelerate AI adoption across the organization. **What We're Looking For** - **7+ years** of software engineering experience with strong expertise in **ML/Python/agents** and **.NET**. - Experience building scalable backend platforms, microservices, distributed systems, and cloud-native applications. - Hands-on experience with **AWS, Kubernetes, Docker, REST APIs, and CI/CD**. - Experience with **LLMs, Agentic AI, RAG architectures, LangChain, LangGraph, Amazon Bedrock, OpenAI, Anthropic**, or similar AI frameworks. - Understanding of AI orchestration, prompt engineering, vector databases, AI security, and observability. - Strong communication, collaboration, and technical leadership skills. **Preferred Skills** - AWS (EKS, Lambda, API Gateway, Bedrock, S3, CloudWatch, IAM) - .NET Core, FastAPI - LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI - MCP (Model Context Protocol), A2A (Agent-to-Agent) protocols - Vector databases (OpenSearch, Pinecone, Weaviate) - OpenTelemetry, LangSmith, Ragas - GitHub Actions, Terraform, Kubernetes **Why Join PAR?** Join a greenfield AI Platform team building the foundation for **enterprise-scale Agentic AI**. You'll help create reusable AI services, multi-agent orchestration, developer platforms, and intelligent automation capabilities that will power the next generation of PAR's restaurant technology products while working with cutting-edge AI technologies and global engineering teams. **Interview Process:** Interview #1: Phone Screen with Talent Acquisition Team Interview #2: Video interview with the Technical Teams (via MS Teams/F2F) Interview #3: Vide…