AI Engineer
JD Power
Job Overview
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Job Description
AI Engineer
You will design, build, and operate production-grade Generative AI solutions that power our products and analytical solutions. You will work across data, models, and applications to deliver reliable AI workflows, integrating large language models with modern data and analytics environments. You will own initiatives end-to-end, including architecture, experimentation, deployment, monitoring, and continuous improvement.
The Impact You Will Have In This Role
You will shape how we apply Generative AI to high-value business problems by building systems that measurably improve customer experience, operational efficiency, and decision quality. You will raise the quality bar for production AI by setting standards for design, safety, evaluation, and operational readiness. You will mentor other engineers and partner with product, data science, and business stakeholders to translate ambiguity into scalable AI capabilities across multiple products and use cases.
What You’ll Be Doing In This Role
- 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.
Qualifications Of This Role
- 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.
- Automotive domain knowledge is a plus, not required.
- Able to travel as needed for customer and internal collaboration.
Key skills/competency
- Generative AI
- Large Language Models (LLMs)
- Python
- SQL
- Data Engineering
- API Integration
- Experimentation Design
- Production Monitoring
- Data Platforms (Databricks, Snowflake)
- Problem Solving
How to Get Hired at JD Power
- Research J.D. Power's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
- Tailor your resume: Highlight your experience with Generative AI technologies, Python, SQL, and modern data platforms to match the AI Engineer role.
- Showcase project impact: Quantify results from shipping and operating LLM-enabled features in production environments.
- Prepare for technical deep-dives: Be ready to discuss data engineering fundamentals, API integrations, and experimentation design for AI solutions.
- Emphasize problem-solving: Discuss how you translate ambiguous business problems into scalable technical architectures and actionable plans.
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