Generative AI Engineer

We’re looking for a hands-on leader to design, develop, and deploy a generative AI platform that integrates seamlessly with enterprise systems. This role requires both technical expertise and strategic vision to build scalable AI-driven applications.

Key Responsibilities:
• Lead the end-to-end development of a robust AI platform, ensuring scalability and efficiency.
• Architect and develop full-stack solutions for AI/ML pipelines, including data ingestion, processing, and model execution.
• Oversee the deployment and management of AI, ML, GenAI, and LLM infrastructure.
• Design, integrate, and test APIs to support AI applications.
• Implement monitoring systems to track model performance, data quality, and infrastructure health.
• Work closely with data scientists, ML engineers, and software developers to streamline AI model integration.
• Collaborate with business teams and stakeholders to align AI development with company goals.
• Ensure security and compliance of AI platforms and APIs.
• Mentor junior engineers and provide technical guidance.
• Maintain documentation and architectural blueprints for operational efficiency.
• Establish best practices for ML pipeline governance and model monitoring.

Required Qualifications:
• Bachelor's or Master’s degree in Computer Science, Engineering, or related field.
• Strong experience in platform development and large-scale system architecture.
• Expertise in cloud engineering, particularly with AI/ML applications.
• Proficiency in full-stack development, including backend, APIs, and front-end technologies like React, Vue, or Angular.
• Hands-on experience with MLOps tools (e.g., MLflow) and cloud-native technologies (Kubernetes, Serverless, PaaS).
• Advanced programming skills, especially in Python, and familiarity with multiple frameworks.
• Deep understanding of Generative AI concepts such as prompt engineering, Retrieval-Augmented Generation (RAG), and model fine-tuning.

Preferred Qualifications:
• Experience building deep learning and LLM-based applications.
• Contributions to open-source projects or research initiatives.