About the job
Join us as a Senior AI Engineer at Tyme, where your expertise in artificial intelligence will help revolutionize banking systems. We are looking for a skilled professional with a robust academic background and extensive technical knowledge, adept at transforming advanced research into practical banking applications. In this pivotal role, 80% of your time will focus on engineering excellence, deploying AI models, optimizing infrastructure, ensuring system reliability, and addressing real-world implementation hurdles. The remaining 20% will involve keeping abreast of the latest AI research and technologies. You will play a critical role in bridging the gap between cutting-edge AI research and scalable production systems in the financial services industry.
Key Responsibilities
- AI Engineering & Deployment (80%)
- Design and implement production-ready AI/ML systems on AWS, emphasizing reliability, scalability, and performance for banking applications.
- Manage MLOps pipelines utilizing AWS services (SageMaker, Bedrock, Lambda, Step Functions) for model versioning, monitoring, and automated retraining workflows.
- Develop and enhance AI solutions utilizing AWS Bedrock, OpenAI API, and Gemini API, integrating Model Context Protocol (MCP) and Agent-to-Agent (A2A) protocols for diverse banking applications.
- Create and refine prompt engineering frameworks and management systems for LLM-based applications.
- Construct graph analysis solutions for fraud detection, customer relationship mapping, and network analysis within the banking sector.
- Debug and troubleshoot AI systems in production, identifying and rectifying issues related to model performance, data pipelines, and AWS infrastructure.
- Establish and maintain AIOps practices, including automated monitoring, alerting, and incident response for AWS-based AI systems.
- Optimize model serving infrastructure for latency, throughput, and cost-effectiveness using AWS services.
- Develop robust data pipelines using AWS Glue, Kinesis, and related services for training and inference.
- Collaborate with software engineering and risk teams to integrate AI functionalities into banking products and services.
- Ensure adherence to banking regulations and security protocols in all AI deployments.
- Monitor model performance in production and implement strategies for drift detection and retraining.
- AI Research & Innovation (20%)
- Keep updated with the latest AI research, evaluating its relevance to banking and financial services.
- Conduct research and prototype new AI architectures and techniques suitable for financial applications.
- Assess innovative approaches in model training, inference optimization, and architectural advancements.
- Share insights through technical discussions, paper reviews, and internal research presentations.
- Identify opportunities to leverage cutting-edge research to enhance fraud detection, customer service, risk assessment, and other banking functions.
