Associate Director (AI Hub GTS)

Role Overview: As an AI Research Scientist, you will be responsible for developing the overarching technical vision for AI systems that meet both current and future business needs. Your role will involve architecting end-to-end AI applications, collaborating with business analysts and domain experts to translate business objectives into technical requirements, and designing agile project roadmaps in alignment with market needs. Additionally, you will work closely with product management to ensure smooth data flows, quality, and governance across various data sources. Key Responsibilities: - Lead the design of reference architectures, roadmaps, and best practices for AI applications - Evaluate emerging technologies and methodologies, recommending innovations for organizational strategy - Define system components such as data ingestion pipelines, model training environments, CI/CD frameworks, and monitoring systems - Streamline deployment and scaling of AI systems using containerization (Docker, Kubernetes) and cloud services - Implement versioning, rollback, and monitoring mechanisms for system stability and reliability - Oversee project management for AI and ML applications, from planning to post-production optimization - Enforce security best practices with a focus on data privacy, user security, and risk mitigation - Provide mentorship to engineering teams and promote a culture of continuous learning Qualifications Required: - Strong background in working with or developing agents using langgraph, autogen, and CrewAI - Proficiency in Python and knowledge of machine learning libraries such as TensorFlow, PyTorch, and Keras - Experience with cloud computing platforms (AWS, Azure, Google Cloud Platform) for building scalable AI solutions - Hands-on skills with containerization (Docker), orchestration frameworks (Kubernetes), and DevOps tools like Jenkins and GitLab CI/CD - Proficiency in SQL and NoSQL databases, expertise in designing distributed systems, RESTful APIs, GraphQL integrations, and microservices architecture - Knowledge of event-driven architectures and message brokers (e.g., RabbitMQ, Apache Kafka) Additional Company Details: This role requires preferred skills in monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack) and familiarity with cutting-edge libraries such as Hugging Face Transformers and OpenAI's API integrations. Experience in large-scale deployment of ML projects and knowledge of DevOps/MLOps/LLM Ops are beneficial for this position. Strong behavioral attributes such as mentoring abilities, project ownership, risk mitigation, and understanding of business objectives are key for success in this role. If you have a Bachelor's or Master's degree in Computer Science, certifications in cloud technologies (AWS, Azure, GCP), TOGAF certification (good to have), and 11 to 14 years of relevant work experience, this AI Research Scientist role could be an ideal fit for you.,