Join our dynamic team as a Senior AI/ML Engineer and play a pivotal role in shaping the future of artificial intelligence within our organization. You will be instrumental in developing and managing advanced ML pipelines, sophisticated GenAI workflows, and intelligent AI-assisted tools. Your contributions will significantly enhance our fraud detection capabilities and drive the broader adoption of AI across all business units.

Our robust data environment includes technologies like Redshift (Bronze/Silver/Gold), EC2, AWS Bedrock, FeatureSpace, and Claude Code/Enterprise. We are transitioning from Confluent to RedPanda for our event streaming needs.

Key responsibilities include building and maintaining robust ML pipelines for fraud detection and other AI initiatives, working under the guidance of senior engineers. You will also support the integration of cutting-edge tools like Claude Code and Claude Enterprise into our engineering processes.

Further, you will develop and manage GenAI and agentic workflows leveraging AWS Bedrock and Claude APIs. This involves contributing to feature engineering, model deployment, and ongoing monitoring pipelines. Collaboration with Data Engineers is crucial for ensuring data readiness and pipeline reliability for ML workloads.

Adherence to responsible AI practices, in line with our Paved Paths governance model, is essential. You will also ensure all AI/ML deliverables comply with PCI DSS and data privacy requirements.

We are seeking candidates with at least 6 years of experience in ML engineering or AI engineering roles. A strong command of Python is essential, including proficiency with ML frameworks such as scikit-learn, PyTorch, or TensorFlow, and expertise in LLM/GenAI tooling.

Experience with AWS ML services, specifically SageMaker and Bedrock, is required. Familiarity with event streaming platforms like Kafka, Confluent, or RedPanda is also necessary. We look for exposure to Claude APIs, RAG architectures, or agentic workflow patterns.

A working knowledge of CI/CD pipelines using Bitbucket or Argo is expected. Additionally, an awareness of PCI DSS and data privacy requirements is crucial for this role.