AI/ML Engineer

  • Closed
  • US Company | Large (251-500 employees)
  • LATAM (100% remote)
  • 2+ years
  • Long-term (40h)
  • Enterprise software
  • Full Remote

Required skills

  • n8n
  • Python
  • Crew AI
  • LangChain
  • Llamalndex
  • Autogen
  • Agentuity

Requirements

Must-haves

  • 2+ years of software engineering experience
  • Experience with applied AI, or automation engineering experience
  • Experience with Python and agentic frameworks (e.g., LangChain, LlamaIndex, AutoGen)
  • Experience designing and deploying agents using tools (e.g., Crew AI, Agentuity, n8n)
  • Proficiency with prompt engineering, memory strategies, and tool/function calling
  • Ability to collaborate across departments to deliver AI solutions and promote adoption
  • Ability to support business stakeholders in adapting workflows to agentic systems
  • Experience managing delivery timelines and defining project success metrics
  • Strong communication skills in both spoken and written English

Nice-to-haves

  • Startup experience
  • Bachelor's Degree in Computer Engineering, Computer Science, or equivalent

What you will work on

  • Design, build, and manage LLM-based agents that automate internal operations across departments (e.g., Engineering, Product, Sales, HR, Field Operations)
  • Identify high-impact use cases and deliver tailored agentic solutions from scoping to scaling
  • Own the full lifecycle of AI-powered automations, ensuring seamless integration and long-term reliability
  • Collaborate with product managers, engineers, and stakeholders to embed agents into real-world workflows
  • Promote adoption by partnering with department leads to evolve processes and drive behavior change
  • Design agentic systems using frameworks (e.g. Crew AI, Agentuity) to support complex workflows
  • Integrate APIs and tools using automation platforms (e.g. n8n, Zapier, Make.com)
  • Implement advanced techniques like prompt chaining, memory strategies, RAG, and tool-calling
  • Monitor, maintain, and optimize deployed agents for performance, uptime, and value delivery
  • Establish governance, testing, and issue resolution processes for production agents
  • Lead agentic project plans, delivery timelines, and milestone tracking
  • Document agent behavior, system logic, testing protocols, and maintenance procedures
  • Report on solution performance, ROI, and progress to leadership and contribute to automation strategy

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