Gen AI Platform Engineer-Assistant Vice President

We are seeking a highly skilled and motivated GenAI Platform Engineer to design, implement, and manage the infrastructure and pipelines that support our generative AI initiatives. The ideal candidate will have a strong background in DevOps practices, combined with expertise in Python and data-intensive technologies like Kafka, Spark, and Redis. You will be responsible for ensuring the reliability, scalability, and efficiency of our AI/ML workflows, from data ingestion and model training to deployment and monitoring.

Key Responsibilities

• Infrastructure as Code (IaC): Design, build, and maintain scalable, secure, and resilient infrastructure for GenAI applications using modern IaC tools and practices.
• CI/CD for MLOps: Develop and manage robust CI/CD pipelines for the complete machine learning lifecycle, including data processing, model training, validation, deployment, and monitoring.
• Data Pipeline Management: Engineer and operate high-throughput, real-time data pipelines using technologies like Apache Kafka and Spark to feed our GenAI models.
• Performance and Caching: Implement and manage distributed caching solutions using Redis to ensure low-latency performance for our AI services.
• Automation: Automate all aspects of the infrastructure and software delivery lifecycle to improve speed and reliability.
• Collaboration: Work closely with data scientists, software engineers, and security teams to create a seamless and secure development and production environment.
• Monitoring & Reliability: Implement comprehensive monitoring, logging, and alerting solutions to ensure the health and performance of the GenAI platform. Proactively troubleshoot and resolve infrastructure and pipeline issues.
• Security: Embed security best practices into the CI/CD pipeline and infrastructure, ensuring compliance with Citi's strict security standards.

Required Skills:

• Programming: Strong proficiency in Python for scripting, automation, and application development.
• DevOps & CI/CD: Extensive experience with DevOps principles and tools. Proven ability to build and manage complex CI/CD pipelines (e.g., using Jenkins, GitLab CI, Tekton, or similar).
• Data Technologies: Hands-on experience with distributed data processing and streaming platforms, specifically Apache Spark and Apache Kafka.
• In-Memory Data Stores: Solid experience with Redis, including its use for caching, session management, and as a message broker.
• Containerization: Deep understanding of container technologies like Docker and container orchestration platforms such as Kubernetes or OpenShift.
• Education: Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field.

Preferred Skills:

• GenAI & MLOps: Experience with the lifecycle of Generative AI models (e.g., LLMs) and familiarity with MLOps principles and tools.
• Cloud Platforms: Experience with public or private cloud platforms (e.g., AWS, GCP, Citi Internal Cloud).
• Observability & Monitoring Tools: Familiarity with observability and monitoring tools like Prometheus, Grafana, Splunk, or the ELK stack.
• Financial Services: Experience working in the financial services industry is a plus but not required.
• Problem-Solving: Excellent analytical and problem-solving skills with the ability to thrive in a fast-paced, collaborative environment.

Education:

• Bachelor’s degree/University degree or equivalent experience

This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.

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