AI Architect

In this role, you will be responsible for AI Architecture Design, where you will develop robust architectures for generative AI solutions, leveraging the latest advancements in foundation models, large language models (LLMs), and multimodal AI. You will also be involved in Model Development, building and fine-tuning advanced generative models, such as GPT-based models, diffusion models, and transformers, for applications in text, image, video, and audio generation. Framework Integration is another key aspect of the role, where you will integrate modern AI frameworks, such as LangChain and LlamaIndex, to enhance the capabilities of generative models in production environments.

Additionally, you will be tasked with implementing Data Strategy, including synthetic data generation, federated learning, and secure data sharing protocols for effective model training. You will design and oversee the deployment of scalable AI systems using the latest technologies, such as MLOps pipelines, container orchestration (Docker, Kubernetes), and serverless architectures. Ensuring Ethics & Compliance is also crucial, where you will make sure AI models comply with ethical guidelines, including responsible AI principles, addressing fairness, transparency, and mitigating bias.

Staying updated with the latest AI trends, such as reinforcement learning with human feedback (RLHF), AI explainability, and continual learning, and applying them to real-world problems is essential. Collaboration is key in this role, as you will work closely with cross-functional teams, including data engineers, scientists, and product managers, to align AI systems with business goals. Leadership & Mentorship are also important aspects, as you will provide guidance to junior AI practitioners and foster a culture of innovation within the team. Performance Monitoring is another critical responsibility, where you will define KPIs for model performance, monitor systems in production, and implement mechanisms for continuous improvement and retraining.

The ideal candidate for this role should have a Bachelors, Masters, or Ph.D. in Computer Science, Artificial Intelligence, Data Science, or related fields, along with 5+ years of experience in AI/ML, with a focus on generative AI technologies. Proven expertise in deploying large-scale generative models in production environments, hands-on experience with AI/ML frameworks such as PyTorch, TensorFlow, and Hugging Face Transformers, and proficiency in Python, R, or Julia for data science and AI model development are required. Additionally, expertise in cloud-native AI solutions, familiarity with advanced data strategies like synthetic data creation and federated learning, and hands-on experience with MLOps practices are preferred. Strong analytical skills, the ability to thrive in a dynamic, fast-paced environment, and a proven track record of working effectively within cross-functional teams are also desired qualities in the ideal candidate.,