Full-Stack Software Data Engineer - Generative AI

Software Data Engineer - Generative AI

Apply locations: GA-Atlanta | Time type:
Full time | Posted on:
Posted Yesterday | Job requisition

At AIG, we are making long-term investments in a brand-new, innovative Generative AI team, designed to explore new possibilities for how artificial intelligence can be applied in insurance and beyond. We need your help to lead this transformation.

With the support and investment needed to explore new frontiers in generative AI, you’ll work alongside talented colleagues, innovating and leading projects that will transform how we manage risk and serve our customers.

This team is central to our vision of the future and the core of our business offering. We will incorporate best-in-class engineering and product management principles. Your guidance and collaboration will be critical to its success. To rapidly advance and innovate, we need your skills and expertise to build and scale world-class products. If you’re excited by the opportunity to create meaningful impact, we’d love to hear from you.

AIG is a leading global insurance organization providing property casualty insurance and other financial services in approximately 190 countries and jurisdictions.

We’re reshaping how the world manages risk, and we invite you to be a key part of that transformation. As our Data Engineering Senior Manager - GenAI, you will have the opportunity to make a meaningful impact, leveraging and further developing your skills to guide groundbreaking AI initiatives. If you’re looking for growth and a role where your contributions shape the future, AIG is the place for you.

As the Software Data Engineer Senior Developer for GenAI, you will lead the design, development, and operationalization of cloud-native big data solutions that enable innovative AI models and analytics. You’ll collaborate across teams to deliver data solutions that drive business insights and value, ensuring scalability and sustainability. This is an exciting opportunity to shape the future of data engineering at AIG, guiding teams through complex data challenges and enabling AI-powered decision-making that will fuel business growth.

• Collaborating with stakeholders to identify and deliver innovative data solutions that meet evolving business needs.
• Building and maintaining cloud-native big data solutions, advanced analytics products, and GenAI models.
• Partnering with data architects and senior engineers to implement best practices, ensuring sustainable and scalable designs.
• Working closely with analytics, application development, and data science teams to foster collaboration and drive innovation.
• Delivering high-quality results on fast-paced schedules while maintaining rigorous standards for development and code management.

• Experience designing, developing, and implementing data processing pipelines using Python and Spark.
• Minimum of 4 years of professional software development experience.
• Strong proficiency in Python, with hands-on experience with Apache Spark and PySpark for large-scale data processing.
• Ability to write clean, efficient, and well-documented Python and Type Script code.
• Experience with testing frameworks (pytest, unittest).
• Proficiency in cloud-native platforms and tools, including Hadoop, HDFS, Spark, Kubernetes, and Elasticsearch.
• Experience with containerization (Docker) and orchestration tools (Kubernetes, Docker Compose).
• Background in deploying and maintaining AI/ML models, with hands-on experience using platforms like Palantir Foundry, Snowflake, and AWS Sage Maker.
• Ability to build and maintain scalable APIs to expose data and functionalities.
• Skills in performance optimization for data workflows, including leveraging containerization for parallel execution.
• Participation in designing data platforms and applications.
• Experience with CI/CD pipelines, version control (Git Hub), and Jenkins.
• Experience setting up end-to-end engineering pipelines, monitoring, and troubleshooting.

Ready to take your career to the next level? We would love to hear from you.