Artificial Intelligence Engineer

***Local candidates only will be considered for this role***We are seeking an experienced AI Engineer to design, build, and deliver production-grade generative AI applications that solve complex business challenges. This role is highly hands-on and ownership-oriented, with end-to-end responsibility spanning solution architecture, development, and deployment.The ideal candidate will serve as a versatile application engineer, translating business requirements into scalable, enterprise-ready GenAI solutions. This position focuses on building practical AI applications and systems rather than core model research or training.ResponsibilitiesDesign and develop generative AI applications from concept through production deployment to address real business and operational needs.Translate business requirements into robust system architectures, selecting appropriate models, frameworks, and integration approaches.Build and maintain full-stack AI-powered applications, including LLM-based tools, internal platforms, and APIs.Implement advanced LLM capabilities such as Retrieval-Augmented Generation (RAG), prompt engineering, tool calling, and agentic workflows.Ensure solutions meet enterprise standards for reliability, security, scalability, and governance.Apply DevOps practices to support CI/CD pipelines, monitoring, containerization, and cloud deployments.Collaborate effectively with cross-functional stakeholders while maintaining strong technical ownership and independent execution.Evaluate emerging generative AI tools and platforms for potential business value.Communicate technical concepts, trade-offs, and recommendations clearly to both technical and non-technical audiences.Required QualificationsBachelor’s degree in Computer Science, Engineering, Information Technology, or a related field.3–5+ years of professional experience in software engineering, AI engineering, or closely related roles.Strong proficiency in Python.Proven track record of building and shipping production-grade software systems.Full-stack development experience (frontend and backend).Hands-on experience with major cloud platforms (AWS, Azure, or GCP) and modern cloud architectures.Solid DevOps background, including CI/CD pipelines, containerization (Docker), and infrastructure automation.Experience designing and integrating with RESTful and other APIs following industry best practices.Proficiency with Git and collaborative development workflows.Excellent problem-solving, systems-thinking, and communication skills.Ability to work independently and effectively in a large, complex enterprise environment.Preferred QualificationsDirect experience building and deploying Large Language Model (LLM) applications in production.Familiarity with agentic frameworks such as LangChain, LangGraph, AutoGen, or similar orchestration tools.Background in the energy, utilities, or industrial sectors.