AI Engineer

Description

Responsibilities

• Design and implement end-to-end AI solutions, from data preparation through deployment, with emphasis on AI search and agentic AI technologies.
• Build and implement solutions using platforms such as CrewAI, Azure AI Foundary and GCP’s AgentSpace, integrating with client systems and processes.
• Implement retrieval-augmented generation (RAG) patterns and other AI search techniques to improve knowledge discovery and decision support.
• Develop production-quality code in Python and related tools for data pipelines, model integration, and API development.
• Collaborate with business stakeholders and consulting teams to translate business objectives into AI solution designs.
• Document and present solutions to technical and non-technical stakeholders in clear and actionable ways.
• Stay current with industry developments in AI, search technologies, and utility applications of AI. Other duties as assigned.
  

Good To Have Skills

• Knowledge and experience in end-to-end AI solution delivery, ideally in consulting or applied industry settings.
• Hands-on experience with Generative AI platforms (CrewAI, Azure OpenAI, Azure AI Foundry, Google Vertex AI / Agent Space).
• Understanding of AI search technologies (vector databases, semantic search, RAG pipelines).
• Proficiency in Python and familiarity with APIs, cloud services, and deployment best practices.
  

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (advanced degree preferred).
• 3 years of experience working with Gen AI and ML technologies, real-world application of AI Agents is a plus
• Experience with cloud platforms (Azure, GCP; AWS experience is a plus).
• Familiarity with the electric utility industry, or interest in applying AI to energy and critical infrastructure a plus
• Understanding of modern software development practices and their application in agentic solution development
• General understanding of LLMs.
  

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