Senior Agentic Ai Engineer

Rebel Athletic•Carrollton, TX

About The Position

What You Will Do Lead the design and implementation of production-grade AI agent systems across the enterprise Architect multi-agent systems that handle complex, multi-step workflows including planning, memory, and tool usage Translate business processes into autonomous, end-to-end AI workflows Build and deploy solutions using Python and modern AI frameworks Establish and standardize tools such as LangChain, CrewAI, AutoGen, n8n, or similar Integrate AI into platforms like NetSuite, Salesforce, and internal applications Build scalable AI infrastructure including orchestration layers, APIs, and event-driven systems Define and implement evaluation frameworks, guardrails, and monitoring for AI systems Rapidly prototype, test, and scale solutions into production environments Mentor engineers and contribute to building Rebel’s internal AI engineering capability Required Qualifications 7+ years of software engineering experience with strong Python expertise 2–3+ years of hands-on experience working with LLMs, generative AI, or autonomous agent systems Proven experience building and deploying AI agents or LLM-powered systems in production environments Strong experience with APIs, system architecture, and production system design Deep understanding of LLM behavior, prompt engineering, and RAG architectures Experience designing multi-step, agent-based workflows including planning, memory, and orchestration Experience integrating AI systems with enterprise platforms such as ERP, CRM, or internal tools Ability to translate complex business problems into practical, scalable AI solutions Demonstrated builder mindset with shipped products, production systems, or a strong GitHub portfolio Preferred Qualifications Experience with LangChain, CrewAI, AutoGen, LlamaIndex, or similar frameworks Experience with vector databases such as Pinecone, Weaviate, FAISS, or Chroma Experience with cloud infrastructure (AWS preferred) and deploying scalable AI systems Knowledge of AI evaluation frameworks, hallucination mitigation, and guardrail design Experience with event-driven architectures and workflow orchestration systems Familiarity with data pipelines, real-time processing, and enterprise data integration Experience building human-in-the-loop systems for critical workflows Core Competencies Ownership - drives initiatives from concept through production and scale Systems Thinking - designs solutions that integrate across complex business environments Execution - moves quickly while maintaining quality and reliability Problem Solving - simplifies complex challenges into scalable solutions Leadership - mentors engineers and elevates team capability Communication - translates technical concepts into business impact Success Measures Delivery of production AI agents that drive measurable impact such as time savings, cost reduction, or revenue growth Ability to take business problems and deliver scalable, production-ready AI solutions Establishment of a repeatable Agentic AI framework across the organization Contribution to high-impact initiatives that drive significant business value Growth and mentorship of Rebel’s internal AI engineering capability Why Rebel Athletic Lead the build-out of a next-generation AI-driven enterprise platform Work on real production systems across sales, operations, and manufacturing Direct exposure to executive leadership and company-wide transformation initiatives Opportunity to define and scale Agentic AI as a core competitive advantage High-impact role with visibility across the entire organization Equal Opportunity Statement Rebel Athletic LLC is an Equal Opportunity Employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, military status, or any other protected characteristic. We also strictly prohibit retaliation against individuals who raise concerns or participate in investigations.

Requirements

7+ years of software engineering experience with strong Python expertise
2–3+ years of hands-on experience working with LLMs, generative AI, or autonomous agent systems
Proven experience building and deploying AI agents or LLM-powered systems in production environments
Strong experience with APIs, system architecture, and production system design
Deep understanding of LLM behavior, prompt engineering, and RAG architectures
Experience designing multi-step, agent-based workflows including planning, memory, and orchestration
Experience integrating AI systems with enterprise platforms such as ERP, CRM, or internal tools
Ability to translate complex business problems into practical, scalable AI solutions
Demonstrated builder mindset with shipped products, production systems, or a strong GitHub portfolio

Nice To Haves

Experience with LangChain, CrewAI, AutoGen, LlamaIndex, or similar frameworks
Experience with vector databases such as Pinecone, Weaviate, FAISS, or Chroma
Experience with cloud infrastructure (AWS preferred) and deploying scalable AI systems
Knowledge of AI evaluation frameworks, hallucination mitigation, and guardrail design
Experience with event-driven architectures and workflow orchestration systems
Familiarity with data pipelines, real-time processing, and enterprise data integration
Experience building human-in-the-loop systems for critical workflows

Responsibilities

Lead the design and implementation of production-grade AI agent systems across the enterprise
Architect multi-agent systems that handle complex, multi-step workflows including planning, memory, and tool usage
Translate business processes into autonomous, end-to-end AI workflows
Build and deploy solutions using Python and modern AI frameworks
Establish and standardize tools such as LangChain, CrewAI, AutoGen, n8n, or similar
Integrate AI into platforms like NetSuite, Salesforce, and internal applications
Build scalable AI infrastructure including orchestration layers, APIs, and event-driven systems
Define and implement evaluation frameworks, guardrails, and monitoring for AI systems
Rapidly prototype, test, and scale solutions into production environments
Mentor engineers and contribute to building Rebel’s internal AI engineering capability