Principal Engineer
Job Purpose
The AI Center of Excellence (AICOE) at Intercontinental Exchange (ICE) is driving innovation by developing and deploying cutting-edge AI/ML solutions across the enterprise. We are seeking a Principal Engineer who will lead the design and implementation of scalable, cloud-native platforms and experiment with emerging AI/ML technologies. This role spans the full lifecycle—from development and architecture to deployment and optimization—enabling ICE to harness the power of data and machine learning for transformative business outcomes.
The ideal candidate is a hands-on technologist with deep expertise in Python, distributed systems, and modern data architectures, combined with a passion for exploring generative AI, large language models (LLMs), and advanced ML frameworks. This position requires strong technical proficiency, problem-solving skills, and the ability to collaborate across engineering, data science, and business teams.
Responsibilities
- Architect and implement cloud-native applications and data platforms optimized for AI/ML workloads.
- Design and build high-performance ETL frameworks, data lakes, and serverless systems using technologies like Apache Iceberg, Delta Sharing, and Databricks.
- Research and prototype emerging AI/ML technologies (e.g., LLMs, generative AI, vector databases) to assess feasibility and business impact.
- Develop and maintain CI/CD pipelines and infrastructure-as-code (Terraform) for seamless deployment of AI/ML models and applications.
- Optimize performance and cost efficiency across ML pipelines and distributed systems.
- Collaborate with data scientists and ML engineers to integrate models into production environments.
- Ensure secure data sharing and compliance with enterprise standards.
- Participate in team exercises to identify and implement areas for continuous improvement.
Knowledge and Experience
- A Bachelor’s degree in Computer Engineering, Computer Science, or other related discipline; or equivalent combination of education and experience that is required for the specific job level.
- 8+ years of software development experience with strong Python expertise.
- Hands-on experience with AWS services (ECS, EMR, Lambda, Athena, DynamoDB) and cloud-native architectures.
- Deep knowledge of modern data lake technologies (Apache Iceberg, Delta Sharing, Databricks Unity Catalog).
- Experience building scalable ETL frameworks and serverless systems.
- Familiarity with ML frameworks (PyTorch, TensorFlow) and interest in LLMs and generative AI.
- Strong understanding of CI/CD tools (Jenkins, GitHub Actions) and infrastructure automation (Terraform).
- Experience with distributed computing and big data technologies (Spark, DuckDB).
Preferred Knowledge and Experience
Exposure to deploying ML models in production environments.
Knowledge of vector databases, feature stores, and real-time inference systems.
Experience with Airflow or AWS Step Functions for orchestration.
Contributions to open-source projects or AI/ML communities.
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