Role Overview
We are seeking a highly skilled Infrastructure Engineer with expertise in AI-driven automation to design, build, and optimize intelligent solutions. The ideal candidate will have hands-on experience integrating large language models and AI platforms into infrastructure workflows, enabling enhanced automation, decision support, and operational efficiency.
Key Responsibilities
- Design and develop AI-powered automation and optimization solutions using platforms such as Microsoft Copilot and Google Gemini.
- Build and integrate intelligent agents, scripts, microservices, and automation frameworks that interface with AI/LLM models for data enrichment and decision-making.
- Develop custom prompts, workflows, and extensions to tailor AI behavior for infrastructure and operational use cases.
- Implement retrieval-augmented generation (RAG) and prompt engineering techniques to enhance AI solution accuracy and relevance.
- Translate complex infrastructure challenges into scalable AI-driven solutions.
- Collaborate with cross-functional teams to drive innovation in infrastructure automation and AI adoption.
- Continuously evaluate emerging AI technologies and apply them to improve system performance and efficiency.
Required Skills and Experience
- Strong experience in infrastructure engineering (cloud, systems, or platform engineering).
- Hands-on experience with AI/LLM integrations, including Microsoft Copilot and Google Gemini.
- Proficiency in scripting and automation using tools such as Python, Bash, PowerShell, Terraform, and/or Ansible.
- Solid understanding of prompt engineering and RAG frameworks.
- Experience working with Google Cloud Platform (GCP).
- Strong analytical and problem-solving skills with the ability to design practical, scalable solutions.
- Ability to work effectively in fast-paced, innovation-driven environments.
Preferred Qualifications
- Experience building production-grade AI-powered automation platforms.
- Familiarity with APIs, microservices architecture, and workflow orchestration.
- Exposure to DevOps, SRE, or platform engineering practices.
