Title:  AI Engineer(P3)

Location: Remote – USA, Canada,Europeor Australia

Reports to:Sr. Director, AI & Innovation

VacancyNew- Internal Posting

The Role:  

You build the full-stack components that power Innovation Crew pilots and prototypes. Under the technical direction of the Principal AI Engineer, in close collaboration with the AI Experience Engineer, you write the backend services, API integrations, data connectors, and frontend implementations that turn AI architectures into working systems. This role has a high ceiling and a fast runway: you will be working alongside engineers at the frontier of AI application development, with hands-on exposure to frontier model APIs, agentic frameworks, Power Agents library development, and JD Power's core data infrastructure. You arrive with strong engineering fundamentals and a genuine appetite for AI systems. You gain deep, production-proven agentic engineering experience. In your first 30 days, you will have your first feature shipped inside a PoC sprint and the codebase oriented. By day 60, you will have your first Power Agents contribution reviewed and merged. By day 90, you will have full implementation ownership of at least one PoCcomponent

How we BuildAgents

The Innovation Crew builds alongside its own AI agent workforce. As AI Engineer, you will contribute to building andmaintainingthose agents: writing the tool integrations, evaluation harnesses, and API connectors that give agents access to JD Power's data and systems. You learn to build for observability from day one - every agent pattern you ship is instrumented, testable, and inspectable. The bar here is not "it worked in the demo" but "it behaves predictably, and we can prove it." When a pattern proves reliable, you contribute it to the Power Agents library, where 400+ engineers & knowledge workers can build on it.

The Impact You Will Have in This Role: 

Innovation Crew pilots only get built because the engineering work that underlies them gets done cleanly and quickly. You are the execution engine that turns architectural direction into working code. You build backend services that connect to Snowflake, API integrations that wire agent outputs to JD Power's core platforms, frontend components the AI Experience Engineer builds on. The pilots you help build will be handed off as operational systems tomaintainingteams within Product Engineering, Engineering, OEM Solutions, Infrastructure, and Internal Platforms. You will contribute directly to the Power Agents library, meaning code you write will be used by engineers & knowledge workers across JD Power.

WhatYou’llBe Doing in This Role:

• Build full-stack features and components for Innovation Crew pilots under the technical direction of the Principal AI Engineer: backend services, REST APIs, data pipeline connectors, and frontend implementations; writing clean, well-documented code oriented toward handoff to maintaining teams within Product Engineering, Engineering, OEM Solutions, Infrastructure, or Internal Platforms.

• Integrate Innovation Crew builds with JD Power's core data infrastructure: Snowflake, internal APIs, cloud platforms, and the API Gateway following published gateway standards and working 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 the direction of the Principal AI Engineer, write tests, instrument traces, and document behavior so every module you contribute is auditable, testable, and reusable by the engineering organization.

• Contribute to the team's AI agent workforce: build tool integrations, evaluation harnesses, and observability instrumentation that give development agents access to JD Power's systems; implement the baseline evals that let the team verify agent behavior is reliable before relying on it.

• Consume and configure frontier model APIs, agentic frameworks (LangGraph,CrewAI, or equivalent), and MCP server integrations as directed; develop hands-onproficiencywith the team's AI engineering stack in a production-adjacent environment with real delivery pressure.

• Collaborate closely with the AI Experience Engineer to bring interface designs to life: implement frontend components, connect UI layers to backend services, and contribute to the sharedcomponentlibrary.

• Support intake technical scoping by mapping integration dependencies, spiking on technical unknowns, and estimating effort;participatein Emerging Technology evaluations by building PoC implementations and contributing benchmark findings to Technology Radar drafts.

Qualifications of this Role:

• Full-stack engineering fundamentals across backend (REST APIs, cloud-native service patterns) and frontend: solid enough to build a working API, connect it to a data source, and surface it through a functional UI - you do not need a dedicated teammate to do either half.

• Genuine, demonstrable curiosity about AI systems: you have built something with an LLM API, understand what RAG and tool-calling mean in practice, follow frontier model developments, and actively use AI coding tools as part of how you work.

• Clean, well-documented code and a fast-learning orientation: this role pairs closely with principal-level engineers who move quickly; you absorb direction, ask sharp questions, and contribute meaningfully without waiting for complete specifications.

Also Valued

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

• RAG patterns, vector databases (pgvector, Pinecone,Weaviate), and basic eval harness design, even if you have only done this in a side project, knowing the concepts matters.

• Observability basics: you know the difference between a trace and a log, have seenLangfuseorLangSmithin use, and understand why instrumentation is part of building, not a post-build step.

• JD Power internal platform or API familiarity; existing knowledge of our data schemas or product ecosystem reduces ramp time significantly.

The Hiring Manager says: 

“I am looking for someone with strong engineering fundamentals and a genuine hunger to apply them to AI systems. You do not need a five-yeartrack record, you need to have built something real with an LLM, have clean code instincts, and be ready to learn fast alongside engineers who are working at the frontier. If you can demo something youactually shipped (an agent, a RAG pipeline, a tool-calling integration, anything where you can walk through what broke and how you fixed it) that tells me everything I need to know.”

This position has a starting salary range of $115,000 - $130,000 USD / $95,000 - $115,000 CADper year. This is the range we reasonably and in good faith expect to pay for the role at the time of posting. An employee’s pay within the range isdeterminedbya number offactors, including relevant skills, education, qualifications, experience, performance, business or organizational needs, and geographic location.

Our Values
We POWER Our Customer’s Success

We are Innovative, Collaborative and Grounded and in Data