AI Engineer

Location

Employment Type

Location Type

Department

Compensation

United States

$200K – $215K • Offers Equity • Offers Bonus

Canada

$150K – $165K • Offers Equity • Offers Bonus

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:

• Canada, Remote

• United States, Remote

Reports To:

• Director, Software Development

What We’re Looking For:

• 5+ years of professional software engineering experience.

• 1+ year shipping AI in production, with ideally a progression from applied ML into Generative AI and agentic solutions.

• 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).

• Strong experience with retrieval and grounding: vector databases plus hybrid retrieval/reranking is a plus.

• 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).

• Strong proficiency in Python and its ecosystem for software development and applied AI.

• Experience with Databricks (Delta Lake, Unity Catalog) and deploying AI services (Model Serving); classic MLOps/MLflow is a plus.

• Strong ability to “glue” systems together via REST or GraphQL APIs.

• Responsible AI experience focused on privacy, security, access control, and defenses against prompt injection and tool misuse.

• Excellent problem-solving skills and ability to work independently in a fast-paced, sometimes ambiguous environment.

• Bachelor’s degree in computer science or a related technical field.

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.

• Familiarity with full-stack implementation (NodeJS and/or Ruby on Rails) is a plus.

• Experience in Fuel and CStore industry, Customer Loyalty, and/or Retail is a strong plus.

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.

• Hands-on Technical Contribution: Act as the applied AI subject matter expert within the organization. Provide technical direction to engineers and stakeholders while actively building and shipping.

• 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.

• Stay Current: Continuously research and evaluate AI advancements, multi-agent orchestration, and agentic autonomy to keep PAR Retail at the leading edge of practical innovation.

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.