AI Engineer

Description of the Role and Key Responsibilities The AI Developer contributes to the design, development, and implementation of AI-driven solutions that address business challenges and enable data-driven decision-making. This role combines hands‑on technical work with strong analytical thinking and client‑focused solutioning, working under the guidance and mentorship of senior AI consultants and architects. Key Responsibilities Writing code (predominantly in Python, along with R, Java, or C++) to implement AI algorithms. Integrating AI models into existing software applications and deploying them into production environments, including cloud platforms such as AWS and Azure. Testing, troubleshooting, and tuning algorithms to improve performance, accuracy, and efficiency. Collaborating with data scientists, software engineers, and stakeholders to translate business needs into effective technical solutions. Assisting in the analysis of business requirements and translating them into AI‑based technical solutions. Developing and enhancing AI applications using Python and Java, with a focus on scalable and maintainable design. Performing data analysis, data cleansing, and exploratory analysis to support AI/ML use cases. Supporting the development and testing of AI models, prompts, and workflows. Adhering to organizational standards, security practices, and responsible AI guidelines. Qualification and Specialization Master’s Degree (preferred) in Engineering, Computer Science, Data Science, Artificial Intelligence, or a related discipline. High proficiency in Python (essential), along with knowledge of Java, C++, or R. Strong understanding of Machine Learning (supervised and unsupervised learning), Deep Learning, Neural Networks, Natural Language Processing (NLP), and Computer Vision. Familiarity with cloud platforms such as AWS, Google Cloud AI, or Microsoft Azure for deployment, along with tools like Docker and Kubernetes. Proficiency in Git and GitHub. Unique Experience from This Role Exposure to AI solution development while working at the intersection of technology and business. Hands‑on experience with OpenAI and generative AI technologies in enterprise use cases. Opportunity to work on real client problems in regulated domains such as healthcare. Experience in data‑driven storytelling, insight generation, and solution recommendations. Practical understanding of responsible AI, governance, and ethical AI practices. Mentorship from experienced AI consultants and architects. Learning Outcomes for the Role Understand how to analyze business problems and map them to AI solutions. Gain practical experience in Python‑based AI development and OpenAI integrations. Learn to perform effective data analysis and insight generation. Develop foundational consulting skills, including requirement analysis, documentation, and stakeholder communication. Build awareness of the AI solution lifecycle—from ideation to deployment. Be prepared to transition into roles such as AI Consultant, Associate AI Engineer, or Generative AI Specialist. #J-18808-Ljbffr University of Denver