Staff Software Engineer – AI Platform
General Motors1 day ago
Warren, MI, USA +2 moreStaff+
Base Salary
$189k - $333k/yr
Responsibilities
- Own architecture and hands-on delivery of complex customer-facing AI modules from product requirements through production.
- Design component boundaries, APIs, data models, ERDs, sequence flows, deployment designs, test strategies, and AI evaluation plans.
- Build reusable services for orchestration, agents, grounding, retrieval, memory, tool integration, conversation state, and channel adapters.
- Lead technical decisions involving inference, serving, reliability, security, observability, capacity, and operational readiness.
- Establish reference implementations and engineering patterns for AI-enabled services across GCP and Azure.
- Drive CI/CD, automated testing, AI evaluation and regression pipelines, release readiness, and production operations.
- Partner with product, security, privacy, data, infrastructure, and application teams on cross-system tradeoffs.
- Provide technical leadership through architecture reviews, design documentation, code reviews, incident analysis, and production-readiness reviews.
- Standardize reusable platform interfaces and simplify duplicated capabilities.
Requirements
- 8+ years of software engineering experience, including ownership of distributed, cloud-native, or customer-facing systems.
- Hands-on experience as a technical architect, staff or principal engineer, or lead programmer delivering production systems at scale.
- Expert Python skills and strong Go and/or Java programming skills.
- Strong knowledge of distributed-system design, service boundaries, APIs, data contracts, asynchronous processing, eventing, caching, consistency, and fault tolerance.
- Production experience with LLM applications, agent orchestration, RAG, embeddings/vector search, tool use, MCP, A2A, and chatbot or workflow systems.
- Experience with low-latency, high-throughput inference and serving, concurrency, autoscaling, traffic management, and cost/performance optimization.
- Cloud and delivery experience with GCP and/or Azure, containers/Kubernetes, IAM, secrets, messaging, managed data services, CI/CD, infrastructure as code, and automated testing.
- Ability to define architecture artifacts and non-functional requirements for security, privacy, observability, SLOs/SLIs, capacity, business continuity, disaster recovery, and operational resilience.
- Strong written and verbal communication, technical judgment, and ability to influence without direct authority.
- Preferred experience building conversational AI for automotive, mobility, contact center, consumer, or other high-scale customer-facing domains.
- Preferred experience with Vertex AI, Azure AI services, model gateways, vector databases, retrieval/evaluation platforms, model observability, privacy-aware personalization, governed memory, auditability, deletion workflows, and enterprise-system integrations.
Benefits
- Health and wellbeing benefits including medical, dental, vision, Health Savings Account, and Flexible Spending Accounts.
- Retirement savings plan, sickness and accident benefits, life insurance, paid vacation and holidays, tuition assistance, and employee assistance program.
- GM vehicle discounts and relocation benefits for candidates who qualify under company policy.
- Hybrid work arrangement requiring the selected candidate to report to a specific location at least three times per week, or as otherwise directed by the manager.
Categories
About General Motors
General Motors designs, manufactures, and sells cars, trucks, and electric vehicles for consumers and commercial fleets under brands including Chevrolet, GMC, Cadillac, and Buick. A public company on the NYSE headquartered in Detroit and founded in 1908, it operates globally and is developing EVs on its Ultium battery platform. Revenue comes from vehicle and parts sales, connected services such as OnStar, and financing through GM Financial.