J.D. Power is a company that unites industry-leading data and insights with world-class technology to solve clients’ toughest challenges. They are seeking an AI Engineer to design, build, and operate production-grade Generative AI solutions that enhance customer experience and operational efficiency. The role involves collaborating with various teams to deliver reliable AI workflows and setting standards for production AI.
Responsibilities:
- Lead the design and implementation of Generative AI services and Agentic workflows that support multiple product features or teams
- Integrate LLMs into applications using modern frameworks, working with APIs or internal model endpoints. Implement telemetry, observability, fallbacks, and cost/latency controls
- Work across data environments to ingest, transform, and serve data for AI use cases, designing practical schemas and retrieval strategies that generalize across environments
- Design and run experiments to compare prompts, models, and configurations; build evaluation flows to measure relevance, safety, robustness, and business impact
- Collaborate with product, data science, design, and domain experts to clarify requirements, break down initiatives into technical plans, and deliver roadmap commitments
- Contribute to and lead code reviews, architecture discussions, documentation, and shared templates/libraries that improve velocity and consistency
- Monitor AI systems in production, participate in incident response, and drive systemic improvements to quality, safety, reliability, and performance
- Partner with security, legal, and compliance to ensure data privacy, responsible AI practices, and regulatory alignment
Requirements:
- Degree in Computer Science, Data Science, Software Engineering or related field
- At least 8yrs of professional experience with a Bachelor's degree or 6 yrs with a Graduate degree
- 1-year experience in Generative AI technologies (included in the overall professional experience), or 1-2 relevant certifications
- Logical, practical, and innovative problem-solving skills. Can turn ambiguity into architecture, milestones, and explicit tradeoffs
- Strong customer-facing communication: able to lead technical discussions, write clear technical documents, and explain solutions to technical and non-technical audiences
- Shipped and operated LLM-enabled features in production, including evaluation, monitoring, and iteration
- Working knowledge of Generative AI quality and safety practices
- Experience building data-intensive systems end-to-end
- Data engineering fundamentals: ingestion/transforms, maintainable schemas, and retrieval/feature pipelines for analytics and AI
- Strong Python and SQL. Experience integrating services via APIs. TypeScript or other strongly typed language experience is a plus. The ability to learn new tools quickly is required
- Hands-on experience with at least one modern data/analytics platform (e.g., Databricks, Snowflake, Palantir Foundry) and the ability to quickly adapt patterns across other environments
- Ownership mindset with high standards for production readiness and customer outcomes
- Able to travel as needed for customer and internal collaboration
- Automotive domain knowledge is a plus, not required