AI Engineer

JD Power is seeking an AI Engineer to join our remote team. You will work under the technical direction of the Principal AI Engineer and in close collaboration with the AI Experience Engineer to build full-stack components that power Innovation Crew pilots and prototypes. You will create backend services, API integrations, data connectors, and frontend implementations that turn AI architectures into working systems. This role offers rapid growth, exposure to frontier model APIs, agentic frameworks, Power Agents library development, and JD Power's core data infrastructure. You should bring strong engineering fundamentals and a genuine interest in AI systems, with hands-on experience in production-quality agentic engineering.

In this role, you will contribute to building and maintaining the team's AI agent workforce by writing tool integrations, evaluation harnesses, and API connectors that access JD Power's data and systems. You will learn to build for observability from day one, ensuring patterns are instrumented, testable, and inspectable. When patterns prove reliable, you will contribute them to the Power Agents library for use by 400+ engineers and knowledge workers.

What you’ll be doing in this role:

• Build full-stack features and components for Innovation Crew pilots under the Principal AI Engineer: backend services, REST APIs, data pipeline connectors, and frontend implementations, with clean, well-documented code that can be handed off to Product Engineering, OEM Solutions, Infrastructure, or Internal Platforms teams.
• Integrate Innovation Crew builds with JD Power's core data infrastructure: Snowflake, internal APIs, cloud platforms, and the API Gateway; coordinate with Internal Platforms to confirm data access, schema conventions, and connection patterns before building.
• Contribute to Power Agents library development: implement new agent patterns under guidance, write tests, instrument traces, and document behavior so modules are auditable, testable, and reusable.
• Support the AI agent workforce: build tool integrations, evaluation harnesses, and observability instrumentation to give agents access to JD Power systems; implement baseline evaluations to verify agent reliability.
• Consume and configure frontier model APIs, agentic frameworks (e.g., LangGraph, CrewAI), and MCP server integrations as directed; develop hands-on proficiency with the AI engineering stack in a production-adjacent environment with real delivery pressure.
• Collaborate with the AI Experience Engineer to bring interface designs to life: implement frontend components, connect UI layers to backend services, and contribute to the shared component library.
• Support intake technical scoping by mapping integration dependencies, exploring unknowns, and estimating effort; participate in Emerging Technology evaluations by building PoC implementations and contributing benchmark findings to Technology Radar drafts.

Qualifications

• Full-stack engineering fundamentals across backend (REST APIs, cloud-native service patterns) and frontend; ability to build a working API, connect to a data source, and surface it through a functional UI without requiring a dedicated teammate for each half.
• Genuine, demonstrable curiosity about AI systems: experience with an LLM API, understanding of RAG and tool-calling concepts, awareness of frontier model developments, and active use of AI coding tools.
• Clean, well-documented code and a fast-learning orientation; ability to absorb direction from principal-level engineers, ask sharp questions, and contribute meaningfully without waiting for complete specifications.

Also valued:

• Python and/or TypeScript; experience with LangChain, LangGraph, or equivalent agent frameworks; familiarity with Snowflake, BigQuery, or similar cloud data platforms.

• RAG patterns, vector databases (e.g., pgvector, Pinecone, Weaviate), and basic eval harness design.

• Observability basics: understanding of traces vs logs, experience with Langfuse or LangSmith, and the importance of instrumentation in building systems.

• Familiarity with JD Power internal platforms or APIs; knowledge of data schemas or product ecosystems reduces ramp time.

• Note: This description reflects the responsibilities and qualifications as described in the posting and does not include salary, contact details, benefits, or other application instructions.