Data Scientist, Principal - AI Product Engineering

Blue Shield of California•Oakland, CA

15h•Hybrid

About The Position

The Data Scientist, Principal works on the AI & Machine Learning team, partnering across the enterprise to apply AI, machine learning, and generative AI to build intelligent products. Reporting to the Director, AI & Machine Learning, this role leads the development and deployment of novel generative AI applications and sets technical direction for AI and machine learning across the organization. The position designs, builds, and ships production-grade AI products, including LLM-powered applications, agents and copilots, retrieval-augmented generation (RAG) and search, and AI-enabled automation embedded in customer-facing products and enterprise workflows. The role translates AI research into real-world products, takes features from 0 to 1, and works across partner teams to deliver solutions and maximize impact. It also includes mentoring team members and contributing to a collaborative, high-performing environment. This is a hybrid role. The workplace model generally requires coming into the office two days each week. Employees living more than 50 miles from an office location will work with their manager to determine in-office time based on business need.

Requirements

Bachelor’s degree in computer science, a quantitative discipline, or equivalent practical experience.
10 years of prior relevant experience in data science, machine learning, applied AI/ML, software engineering, or advanced analytics.
Proven track record of rapidly building and shipping software products, beyond developing models or analyses.
Strong software engineering skills and proficiency in Python, including building APIs and backend services.
Experience leading ML design and optimizing ML infrastructure, model deployment, evaluation, and data processing, and working with machine learning frameworks and libraries.
Hands-on experience with deep learning and LLM application frameworks, including PyTorch, TensorFlow, LangChain, and LangGraph.
Hands-on experience building applications that leverage generative AI models, including prompt engineering and retrieval-augmented generation (RAG).

Nice To Haves

Master’s degree or PhD; advanced degrees in a relevant field may be considered in lieu of a portion of the required experience.
Experience with generative AI research or applications.
Experience designing agent-based systems and orchestration frameworks.
Experience with cloud computing platforms and infrastructure such as Azure, Google Cloud, or AWS, and scalable data processing with SQL or Spark.
Solid MLOps and LLMOps practices, including CI/CD, monitoring, and model lifecycle management.
Experience rapidly developing and shipping software in a fast-paced, customer-facing environment while adapting to changing priorities.
Understanding of responsible AI and governance for regulated or healthcare environments.

Responsibilities

Lead the development and deployment of novel applications leveraging generative AI models, setting technical direction for AI and machine learning across the organization.
Design and develop scalable generative AI applications, including LLM applications, copilots, agents, RAG, and search, for customer-facing products and enterprise workflows.
Rapidly prototype new features and iterate based on evaluation results.
Lead architecture and development of new products and features from 0 to 1.
Collaborate with researchers and product managers to translate AI research into product features.
Build APIs, services, and data and retrieval pipelines that expose AI capabilities to applications.
Optimize software performance and ensure the reliability of deployed applications.
Champion best practices for building and deploying generative AI applications.
Evaluate model performance, analyze results, and implement improvements while ensuring responsible and compliant AI.
Mentor and develop team members, fostering a collaborative and high-performing environment.