H-1B Visa Genai Software Engineer Jobs
GenAI Software Engineer roles sit squarely within H-1B visa specialty occupation territory, requiring at least a bachelor's degree in computer science, AI, or a related field. Employers filing LCAs for these positions typically use SOC codes tied to software development or machine learning, which affects your prevailing wage level and petition strength.
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Get Access To All JobsWho We Are
Nuro is a self-driving technology company on a mission to make autonomy accessible to all. Founded in 2016, Nuro is building the world’s most scalable driver, combining cutting-edge AI with automotive-grade hardware. Nuro licenses its core technology, the Nuro Driver™, to support a wide range of applications, from robotaxis and commercial fleets to personally owned vehicles. With technology proven over years of self-driving deployments, Nuro gives the automakers and mobility platforms a clear path to AVs at commercial scale, empowering a safer, richer, and more connected future.
About the Team
We empower engineers to build the future of transportation by transforming how software is developed, tested, and operated using Generative AI and agentic systems. Our team builds the AI infrastructure that enables autonomous coding agents, intelligent assistants, and autoresearch systems across the engineering lifecycle — from code generation and CI/CD to debugging, knowledge discovery, and ML model improvement. We sit at the intersection of engineering productivity and ML advancement, building platforms and self-improving systems that accelerate both.
About the Role
As a Software Engineer in GenAI Infrastructure & Agent Systems, you will design and build platforms that significantly improve developer productivity and ML research velocity. This role spans:
- Agent infrastructure (harnesses, sandboxes, plugin frameworks, MCP integrations) enabling reliable, production-grade AI agents
- Autoresearch systems that run experiments, evaluate results, and propose improvements to core ML models
You’ll work across the stack — from cloud infrastructure and isolation to agent memory, evaluation frameworks, and developer-facing tools.
About the Work
Build AI agent infrastructure
- Design agent orchestration, sandboxing, and isolation systems
- Develop skill/plugin frameworks and integrate internal tools (e.g., CI/CD, code, observability systems)
- Scale compute infrastructure for agent workloads (GCP, Kubernetes)
Develop autoresearch systems
- Build self-improving agents that run experiments, analyze results, and iterate
- Implement memory, feedback loops, and long-horizon reasoning
- Integrate with ML training, evaluation, and data pipelines
Create AI-powered engineering tools
- Build assistants for support, triage, and workflow automation
- Develop tools for code generation, debugging, testing, and PR review
- Detect and resolve performance and reliability issues automatically
Improve quality and developer workflows
- Design evaluation and observability systems for agent performance
- Integrate agents into CI/CD for testing, failure attribution, and remediation
- Build knowledge systems for search, retrieval, and reuse
About You
- 4+ years of industry experience; BS/MS in Computer Science or equivalent practical experience
- Strong programming skills in Python, C++, or Go, with experience building scalable, reliable systems
- Solid background in cloud infrastructure (GCP/AWS), Kubernetes, CI/CD, and developer tooling
- Passion for building production-grade AI agent systems and improving engineering efficiency through automation
- Interest in autonomous, self-improving systems and ML-driven workflows
- Strong systems thinking across infrastructure, memory, and tooling, with ability to work end-to-end
Preferred:
- Experience with LLM/agent systems in production (tool use, orchestration, sandboxing)
- Familiarity with autonomous agent patterns (memory, reflection, planning)
- Experience with MCP, plugin/skill frameworks, or similar architectures
- Background in ML infrastructure (training pipelines, evaluation, experimentation)
- Experience in DevEx/platform engineering, observability, or security isolation patterns
At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected base pay range is between $160,360 and $240,540 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package.
At Nuro, we celebrate differences and are committed to a diverse workplace that fosters inclusion and psychological safety for all employees. Nuro is proud to be an equal opportunity employer and expressly prohibits any form of workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other legally protected characteristics. #LI-DNP
Who We Are
Nuro is a self-driving technology company on a mission to make autonomy accessible to all. Founded in 2016, Nuro is building the world’s most scalable driver, combining cutting-edge AI with automotive-grade hardware. Nuro licenses its core technology, the Nuro Driver™, to support a wide range of applications, from robotaxis and commercial fleets to personally owned vehicles. With technology proven over years of self-driving deployments, Nuro gives the automakers and mobility platforms a clear path to AVs at commercial scale, empowering a safer, richer, and more connected future.
About the Team
We empower engineers to build the future of transportation by transforming how software is developed, tested, and operated using Generative AI and agentic systems. Our team builds the AI infrastructure that enables autonomous coding agents, intelligent assistants, and autoresearch systems across the engineering lifecycle — from code generation and CI/CD to debugging, knowledge discovery, and ML model improvement. We sit at the intersection of engineering productivity and ML advancement, building platforms and self-improving systems that accelerate both.
About the Role
As a Software Engineer in GenAI Infrastructure & Agent Systems, you will design and build platforms that significantly improve developer productivity and ML research velocity. This role spans:
- Agent infrastructure (harnesses, sandboxes, plugin frameworks, MCP integrations) enabling reliable, production-grade AI agents
- Autoresearch systems that run experiments, evaluate results, and propose improvements to core ML models
You’ll work across the stack — from cloud infrastructure and isolation to agent memory, evaluation frameworks, and developer-facing tools.
About the Work
Build AI agent infrastructure
- Design agent orchestration, sandboxing, and isolation systems
- Develop skill/plugin frameworks and integrate internal tools (e.g., CI/CD, code, observability systems)
- Scale compute infrastructure for agent workloads (GCP, Kubernetes)
Develop autoresearch systems
- Build self-improving agents that run experiments, analyze results, and iterate
- Implement memory, feedback loops, and long-horizon reasoning
- Integrate with ML training, evaluation, and data pipelines
Create AI-powered engineering tools
- Build assistants for support, triage, and workflow automation
- Develop tools for code generation, debugging, testing, and PR review
- Detect and resolve performance and reliability issues automatically
Improve quality and developer workflows
- Design evaluation and observability systems for agent performance
- Integrate agents into CI/CD for testing, failure attribution, and remediation
- Build knowledge systems for search, retrieval, and reuse
About You
- 4+ years of industry experience; BS/MS in Computer Science or equivalent practical experience
- Strong programming skills in Python, C++, or Go, with experience building scalable, reliable systems
- Solid background in cloud infrastructure (GCP/AWS), Kubernetes, CI/CD, and developer tooling
- Passion for building production-grade AI agent systems and improving engineering efficiency through automation
- Interest in autonomous, self-improving systems and ML-driven workflows
- Strong systems thinking across infrastructure, memory, and tooling, with ability to work end-to-end
Preferred:
- Experience with LLM/agent systems in production (tool use, orchestration, sandboxing)
- Familiarity with autonomous agent patterns (memory, reflection, planning)
- Experience with MCP, plugin/skill frameworks, or similar architectures
- Background in ML infrastructure (training pipelines, evaluation, experimentation)
- Experience in DevEx/platform engineering, observability, or security isolation patterns
At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected base pay range is between $160,360 and $240,540 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package.
At Nuro, we celebrate differences and are committed to a diverse workplace that fosters inclusion and psychological safety for all employees. Nuro is proud to be an equal opportunity employer and expressly prohibits any form of workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other legally protected characteristics. #LI-DNP
See all 6,302+ H-1B Visa Genai Software Engineer Jobs
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Get Access To All JobsTips for Finding H-1B Visa Sponsorship as a Genai Software Engineer
Map your credentials to SOC codes
GenAI roles get filed under varying SOC codes depending on the employer. Check O*NET to confirm which occupation code aligns with your specific duties, since mismatches between your degree field and the SOC code are a common RFE trigger.
Target employers with active LCA filings
Use Migrate Mate to filter GenAI Software Engineer roles by employers who have filed recent H-1B LCAs. DOL disclosure data shows filing history by occupation, so you're not guessing which companies actually sponsor.
Verify prevailing wage before negotiating
Run the OFLC Wage Search using the relevant SOC code and your target metro area before you get to offer stage. Your offered salary must meet the certified LCA wage level, and Level I or II designations for AI roles vary significantly by location.
Document your GenAI specialization clearly
Specialty occupation requires a direct relationship between your degree and the role. If your degree is in a general field like computer science, build a portfolio that ties specific coursework or published work to large language models, RAG architectures, or transformer fine-tuning.
Ask about cap-exempt employer status early
Universities, nonprofit research organizations, and certain government-affiliated labs are cap-exempt, meaning your H-1B doesn't enter the annual lottery. If you're open to those settings, confirm cap-exempt status before the offer stage to understand your timeline.
Align your start date with the fiscal year cap
If your employer is cap-subject, USCIS opens H-1B registration in March for an October 1 start. Build your job search timeline so you have an offer in hand before the registration window closes, since missing it means waiting another full year.
H-1B Visa Genai Software Engineer: Frequently Asked Questions
Does a GenAI Software Engineer role qualify as an H-1B specialty occupation?
Yes, GenAI Software Engineer roles meet the specialty occupation standard because they require theoretical and practical application of highly specialized knowledge, typically grounded in a bachelor's degree or higher in computer science, artificial intelligence, or a closely related field. USCIS evaluates whether the specific duties, not just the job title, require that degree-level expertise.
How do I find employers actively sponsoring H-1B visas for GenAI roles?
Migrate Mate surfaces employers with verified H-1B LCA filing history filtered by occupation, so you can see which companies have sponsored roles matching GenAI Software Engineer duties. DOL disclosure data is public, but searching it manually requires downloading large datasets. Migrate Mate organizes that data so your search focuses on employers who already sponsor.
Can I transfer my H-1B to a new GenAI employer without losing my place in the queue?
Yes. Under H-1B portability rules, you can begin working for a new employer as soon as your transfer petition is filed, provided you're maintaining valid status. You don't restart the lottery. The new employer files a new I-129 petition, and if you've accumulated time on your current H-1B, that period carries over toward the six-year cap.
What SOC code do employers typically use when filing H-1B LCAs for GenAI Software Engineer positions?
Most employers file under SOC 15-1252 (Software Developers) or 15-2051 (Data Scientists), though some use 15-1299 (Computer and Information Research Scientists) for research-heavy GenAI roles. The SOC code determines the prevailing wage the employer must certify on the LCA. You can verify the most accurate match for your specific duties using O*NET before the employer files.
Does premium processing make sense for a GenAI Software Engineer H-1B petition?
Premium processing guarantees USCIS adjudicates your I-129 within 15 business days. For GenAI roles where the employer wants you to start quickly, or where your OPT or grace period is expiring, it's often worth requesting. Not all employers cover the fee by default, so it's reasonable to raise it during offer negotiation if your timeline is tight.