1 month ago

Agentic AI Engineer

Numiq

Hybrid
Contractor
$120,000
Hybrid

Job Overview

Job TitleAgentic AI Engineer
Job TypeContractor
Offered Salary$120,000
LocationHybrid

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Job Description

Agentic AI Engineer (Freelance / Contract) at Numiq

Numiq is seeking a skilled Agentic AI Engineer to design and build production-grade AI systems for internal workflows. This is a hands-on role focused on creating reliable, scalable AI tools for real business applications.

Role Overview

You will architect and deploy agentic AI systems capable of multi-step reasoning, tool interaction, and automation of complex workflows. The goal is to develop end-to-end systems delivering consistent, high-quality outputs, moving beyond simple prompts.

Key Responsibilities

  • Design and implement agent-based workflows for financial analysis, insight generation, research, decision support, and business process automation.
  • Build and manage multi-step reasoning pipelines and tool-using agents with memory and planning capabilities.
  • Develop Retrieval-Augmented Generation (RAG) systems.
  • Integrate AI systems with APIs, databases, third-party tools, and internal data environments.
  • Ensure all AI outputs are structured, reliable, and production-ready.

Engagement Structure

  • Freelance / contract role, initially part-time, with potential for scope expansion.
  • Fully remote position with direct collaboration with the founder.
  • Project-based execution with possibilities for long-term engagement.

Key skills/competency

  • Agentic AI Engineer
  • AI Systems Design
  • Production-Grade AI
  • Multi-step Reasoning
  • Tool-Using Agents
  • Retrieval-Augmented Generation (RAG)
  • API Integration
  • Workflow Automation
  • Scalable AI Tools
  • Freelance AI Development

Tags:

Agentic AI
AI Engineer
Freelance
Contract
AI Development
RAG
Workflow Automation
Remote Work
AI Systems
Numiq

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How to Get Hired at Numiq

  • Tailor your resume: Highlight experience in agentic AI, RAG, and workflow automation for Numiq.
  • Showcase projects: Include examples of production-grade AI systems you've built.
  • Prepare for technical questions: Be ready to discuss AI architecture and implementation details.
  • Demonstrate remote work capability: Emphasize strong communication and self-management skills.

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