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AI Engineer

Description

We are seeking a highly skilled AI Engineer to join our growing team. The ideal candidate will have hands-on experience designing, developing, and deploying AI-powered solutions using modern Large Language Models (LLMs), AI coding assistants, workflow automation platforms, and agentic AI systems.

This role requires someone who is passionate about emerging AI technologies and capable of building scalable, production-ready AI applications that improve business operations, engineering workflows, and user experiences.

Responsibilities

  • Design, develop, and deploy AI-powered applications and intelligent automation solutions.
  • Build and maintain AI agents using modern LLM frameworks and orchestration tools.
  • Develop AI-assisted software solutions leveraging tools such as Claude Code and other AI coding platforms.
  • Create automated workflows and integrations using n8n and related automation technologies.
  • Integrate AI models through APIs from leading providers including Anthropic, OpenAI, Google, and others.
  • Develop prompt engineering strategies and optimize AI system performance.
  • Build Retrieval-Augmented Generation (RAG) systems and knowledge-based AI assistants.
  • Collaborate with engineering, operations, and business teams to identify automation opportunities.
  • Monitor, evaluate, and continuously improve AI model outputs, reliability, and efficiency.
  • Stay up-to-date with emerging AI technologies, coding frameworks, and industry best practices.

Minimum requirements

  • 3+ years of experience in software engineering, AI engineering, machine learning, or related fields.
  • Strong understanding of Large Language Models (LLMs) and Generative AI technologies.

Hands-on experience with:

  • Claude Code
  • n8n
  • AI agent frameworks
  • Prompt Engineering
  • API integrations

Experience working with modern AI development ecosystems, including:

  • Anthropic Claude
  • OpenAI GPT models
  • Gemini
  • Cursor
  • Windsurf
  • AI-powered development tools
  • Knowledge of Retrieval-Augmented Generation (RAG) architectures.
  • Experience integrating vector databases and knowledge management systems.
  • Strong programming skills in Python.
  • Familiarity with Git, GitHub, CI/CD pipelines, and cloud environments.
  • Experience building production-grade AI workflows and automations.

Preferred Qualifications

  • Experience with LangChain, LangGraph, CrewAI, AutoGen, or similar agent frameworks.
  • Experience with MCP (Model Context Protocol).
  • Knowledge of AI evaluation, observability, and monitoring tools.
  • Experience with vector databases such as Pinecone, Weaviate, Chroma, or Qdrant.
  • Familiarity with cloud platforms (AWS, Azure, or GCP).
  • Experience building multi-agent AI systems.
  • Understanding of AI security, governance, and responsible AI practices