AI Solutions Engineer

Required Skills AI/ML Development: Understanding of artificial intelligence and machine learning frameworks. Generative AI & LLM Pipelines: Building and deploying solutions for text generation, automation, intelligent search, RAG systems. Cloud AI Platforms: Using Azure AI, Vertex AI, AWS SageMaker for model training and deployment. Automation & Workflow Optimization: Automating university processes and system integration. Git Version Control: Codebase management, collaboration, version tracking. API Integration: Third-party API and service integration expertise. Azure DevOps: Project management and deployment pipeline experience. Project & Deadline Management: Strong ability to manage project timelines effectively, prioritize tasks, and deliver high-quality code. Complex Database Queries: Query development and optimization proficiency. Dashboards & Reports: Generating insightful reports and stakeholder dashboards. Communication & Collaboration: Cross-functional team effectiveness with developers, designers, stakeholders. Leadership & Mentorship: Developer guidance on best practices and emerging technologies

Desired Candidate Profile

Bachelor's degree in computer science, engineering, AI, data science, or related field. 4-5 years of AI development experience with server management and Git version control. Expertise in Python, TensorFlow, PyTorch, n8n, LLM platforms, OpenAI, Azure AI, or Google Vertex AI. Docker/Kubernetes deployment experience. API integration knowledge (RESTful and SOAP). Azure DevOps proficiency for CI/CD pipelines. High commitments in deadline management and prioritization in a fast-paced environment. Database design and query optimization skills. Reporting tools and dashboard experience. Strong communication and cross-functional collaboration abilities. Leadership and junior developer mentoring experience. Strong attention to detail and a commitment to delivering high-quality code. Preferred Qualifications Master's or bachelor's degree in computer science/engineering. Certifications in AI, cloud platforms, Laravel, Azure, or Git. Docker/Kubernetes containerization experience. Machine learning algorithm knowledge. AI-driven project experience. Open-source contributions or developer community participation.