Jobs / United States / General Motors Company
Staff Software Engineer – AI Platform
General Motors Company · 🇺🇸 3 Locations
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 606 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 267 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What General Motors Company paid sponsored hires in similar roles1 certified filing for “AI/ML Engineer” (Software Developers) in MA: $187k–$187k, median $187k. Most were filed at wage level II (100%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — General Motors Company
The US Department of Labor certified 606 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 267 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for General Motors Company →
About the role
Job Description At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We’re turning today’s impossible into tomorrow’s standard —from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features. Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale The Role: We are looking for a Staff Individual Contributor who combines exceptional software-engineering execution with enterprise architecture leadership to design and build the next generation of customer-facing AI systems. This role will lead the architecture and hands-on implementation of reusable modules for conversational AI, agent orchestration, grounding, memory, tool integration, policy enforcement, and AI platform services. The successful candidate will help establish durable technical patterns across cloud services and customer experiences while personally contributing production code in Python and Go and/or Java. This is a senior technical leadership role, not a people-management position. The engineer will influence architecture, mentor through technical leadership, raise engineering standards, and drive execution through design reviews and implementation—not through direct reports. What You'll Do: • Own architecture and hands-on delivery of complex customer-facing AI modules from PRD through production. • Turn product needs into clear 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 for 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 to resolve cross-system tradeoffs. • Provide technical leadership through architecture reviews, design documentation, code reviews, incident analysis, and production-readiness reviews. • Identify opportunities to simplify duplicated capabilities and standardize reusable platform interfaces. Your Skills & Abilities (Required Qualifications): • 8+ years of software engineering experience, including ownership of distributed, cloud-native, or customer-facing systems. • Track record as a hands-on technical architect, staff/principal engineer, or lead programmer delivering production systems at scale. • Expert Python and strong Go and/or Java programming skills. • Strong command of distributed-system design, service boundaries, API and 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-based systems, including quality, safety, grounding, and regression evaluation. • Experience with inference and serving for low latency, high throughput, 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 and implement