This role pays less than
54%
of similar roles. Most pay
$162,000–$246,237
— the shaded band above.
At the midpoint, this role pays about
$196k
versus about
$204k
for comparable roles.
Based on 240 similar postings.
Employer
About General Motors (GM)
General Motors (GM) is a leading American multinational automotive corporation founded in 1908 and headquartered in Detroit, Michigan.
General Motors (GM) currently has
116 open roles
on FindRole.
Listed pay typically runs
$160,200–$245,000
across 59 roles with salary data.
Staff AI Engineer – Analytics & Domain Intelligence
The Staff AI Engineer joins the team to build next-generation analytics experiences using telematics, aftersales, and energy data. This role focuses on transforming complex, governed datasets into natural-language intelligence that allows users to ask business questions without needing to know underlying schemas or SQL. You will design multi-agent systems, orchestration patterns, and reusable AI services while developing retrieval, grounding, reasoning, and evaluation patterns to ensure accuracy and trust. The ideal candidate possesses over eight years of experience in software engineering or AI engineering, with deep expertise in Python, SQL, and semantic engineering. You will work within major cloud environments like Azure, AWS, or GCP to build production-ready systems. Key technical tools include Databricks, LangChain, and LangGraph. This role solves the challenge of turning large-scale distributed data into actionable insights for diverse internal stakeholders.
What does a AI Engineer earn?
Median $211200 from 132 postings across 36 companies.
Build AI-powered analytics experiences using governed data products and domain context.
Design and develop multi-agent systems, orchestration patterns, and reusable AI services.
Create natural-language interfaces that allow users to query complex data without SQL or schema knowledge.
Implement retrieval, grounding, reasoning, memory, and evaluation patterns to ensure answer accuracy.
Develop frameworks that enable domain experts to improve business intelligence without deep AI expertise.
Use platform telemetry and feedback loops to optimize system performance, reliability, and cost efficiency.
Partner with data product teams to integrate high-quality, contract-backed datasets into AI systems.
What we're looking for
8+ years of experience in software engineering, AI engineering, data platforms, or related fields with senior or staff-level leadership.
Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, or a related technical field (or equivalent practical experience).
Proven experience building production AI applications, agentic systems, or LLM-powered analytical experiences.
Strong Python engineering skills and exceptional SQL skills.
Experience building and operating production systems in major cloud environments like Azure, AWS, or GCP.
Strong understanding of semantic engineering, analytical data products, and how they influence AI answer quality.
Experience with Databricks, Unity Catalog, Agent Bricks, LangGraph, LangChain, LangSmith, or similar technologies (preferred).
Experience with RAG, MLOps, monitoring, and feedback loops for AI systems (preferred).