Llm Engineer Jobs in USA with Visa Sponsorship
LLM engineer roles sit squarely in H-1B visa specialty occupation territory, and the strongest sponsors are AI labs, cloud platforms, and enterprise software companies already filing LCAs for ML and software engineering titles. F-1 OPT and STEM OPT cover your first three years while you target employers with active filing history. For detailed occupation requirements, see the O*NET profile.
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Get Access To All JobsINTRODUCTION
Help define the future of hardware development! At AllSpice, we're building the automation engine that powers the next generation of circuit design, enabling breakthroughs in smart vehicles, robotics, rockets, IoT, medical devices, and more. We're creating the agile development environment for hardware engineers with a Git-friendly translation layer and automated CI/CD framework for native circuit designs. Think GitHub/GitLab + Copilot for electronics. Our mission is to bring the same modern workflows that revolutionized software: version control, automation, and collaboration to the hardware world. Learn more about our journey in TechCrunch and our recent Series A announcement. If you're passionate about building tools that empower teams and delight customers, and you want to shape the foundation of modern hardware DevOps, we'd love to meet you!
ROLE AND RESPONSIBILITIES
This is a senior, high-impact software engineering role at the intersection of AI platform development, data engineering, and full-stack product development. You will own the tooling, evaluation systems, and data platforms that make AllSpice's Generative AI team more effective. Your primary users will be internal engineers and product managers, with opportunities to build customer-facing experiences where they support our AI products. We’re looking for someone who can identify the right problems, make thoughtful technical decisions, and take solutions from discovery through implementation, adoption, and ongoing improvement. As you build domain knowledge and establish the AI platform foundation, we’d also like you to grow into contributing directly to AllSpice’s core product alongside the product engineering team. This is an aspirational growth opportunity, not a prerequisite or the role’s initial primary focus.
You will:
- Partner with engineers and product managers to discover workflow bottlenecks, prioritize the highest-impact problems, and own solutions end-to-end—from requirements and architecture to rollout and iteration.
- Own the evaluation and observability layer for our AI products, including automated and human review workflows, regression detection, and comparisons across models, prompts, and pipelines. Make quality, cost, latency, usage, and customer outcomes visible and actionable.
- Build usable internal applications and self-service tools that help engineers and product managers inspect AI results, investigate failures, and provide feedback. Where useful, extend these capabilities into customer-facing experiences.
- Build and maintain scripts, reliable data pipelines, and integrations that connect internal systems, third-party services, LLMs, and Model Context Protocol (MCP) tools, with attention to data quality, schema evolution, and customer data privacy.
- Write clear documentation and communicate findings to both technical and non-technical audiences, including leadership and customers.
- Champion code quality, testing, and reliability across the tooling stack through reviews, mentorship, and thoughtful design.
Example Projects
- Build an internal evaluation workspace for DRCY, our AI design review product, that captures run configurations, inputs, outputs, and telemetry; compares model and prompt changes; and tracks quality, false positives, cost, and latency over time.
- Develop review workflows that let engineers and product managers inspect AI-generated findings, apply scoring rubrics, override automated scores, and investigate regressions—with opportunities to surface relevant insights and feedback workflows to customers.
- Create and maintain data pipelines that aggregate evaluation results, customer feedback, and telemetry into a unified analytics layer.
- Build scripting tools and automations to streamline the Gen AI team's development and testing workflows (e.g., batch evaluation runs, report generation).
- Design and implement RAG-based information repositories and tooling to capture component data and domain knowledge for use by our suite of AI products.
- Integrate with CI/CD systems (GitHub Actions) to surface AI insights directly in engineering workflows.
- Partner with infrastructure to measure cache effectiveness, usage, and cost, and use those insights to improve the reliability and efficiency of AI workflows.
- As an aspirational next step, contribute directly to core AllSpice product features—for example, integrating AI review findings and feedback into existing engineering workflows—in partnership with the product engineering team.
OUR STACK
- Languages: Python, TypeScript/JavaScript, SQL
- Analytics & Data: SQL databases (Postgres), Jupyter Notebooks, business intelligence/analytics tools
- AI/LLM: Langchain, Pydantic AI, Langfuse
- Web: Vue/TypeScript front-end, common web architectures and APIs
- Infrastructure: GitHub Actions for CI/CD, Docker Swarm & Terraform, AWS
- Our Hub application is a soft fork of Gitea + Go [server-side] + Vue/TypeScript Front-end
BASIC QUALIFICATIONS
Our ideal candidate should have the following:
- 4+ years of software engineering experience with a focus on tooling, data platforms, or full-stack web development, with demonstrated senior-level ownership of systems or products that other people depend on.
- Strong SQL skills and experience designing data pipelines and storage schemas, handling data quality and schema evolution, and using data/analytics tools (e.g., Jupyter, Metabase, Looker, or similar BI platforms).
- Proficiency in Python scripting and automation for data pipelines, integrations, and internal tools.
- Experience building web applications or customer-facing tools using modern frameworks (e.g., Vue, React, TypeScript).
- Practical experience shipping or maintaining LLM-enabled systems and building infrastructure around them, such as evaluation pipelines, observability, or integrations. You understand non-determinism, quality and reliability challenges, and tradeoffs across cost, latency, and model performance.
- Excellent communication skills — you can translate technical findings into clear insights for engineers, product managers, and customers alike.
- A customer-first mindset: you think about the end-user experience and proactively seek feedback to improve the tools you build.
- Bachelor's degree or higher in a technology-related field, or equivalent practical experience.
- Project management skills with the ability to lead and collaborate with varied stakeholders to move projects forward.
- Comfort with ambiguity and autonomy: you independently identify problems, propose solutions, make pragmatic build-vs.-buy and architectural decisions, and bring stakeholders along in a fast-moving environment.
PREFERRED QUALIFICATIONS
(Preferred) Availability to work out of our flex offices in San Francisco or Boston on a hybrid basis (2–3 times/week), but we are flexible for the right candidate.
RELEVANT SKILLS
You don't necessarily have to be proficient in all of these, but the more you know, the better:
- Python, TypeScript, SQL
- Business analytics and data visualization tools
- Langchain, Pydantic AI, and LLM evaluation frameworks
- GitHub Actions development and CI/CD
- Common web architectures, APIs, and front-end frameworks (Vue, React)
- Monitoring and observability tools (e.g., Langfuse, DataDog, Grafana)
- Project management and stakeholder communication
BENEFITS
- Supportive and smart colleagues, flexible work, opportunity to make a big impact, competitive salary & equity, health, dental, vision, generous PTO, home office stipend.
COMPENSATION RANGE
$160K - $190K
INTRODUCTION
Help define the future of hardware development! At AllSpice, we're building the automation engine that powers the next generation of circuit design, enabling breakthroughs in smart vehicles, robotics, rockets, IoT, medical devices, and more. We're creating the agile development environment for hardware engineers with a Git-friendly translation layer and automated CI/CD framework for native circuit designs. Think GitHub/GitLab + Copilot for electronics. Our mission is to bring the same modern workflows that revolutionized software: version control, automation, and collaboration to the hardware world. Learn more about our journey in TechCrunch and our recent Series A announcement. If you're passionate about building tools that empower teams and delight customers, and you want to shape the foundation of modern hardware DevOps, we'd love to meet you!
ROLE AND RESPONSIBILITIES
This is a senior, high-impact software engineering role at the intersection of AI platform development, data engineering, and full-stack product development. You will own the tooling, evaluation systems, and data platforms that make AllSpice's Generative AI team more effective. Your primary users will be internal engineers and product managers, with opportunities to build customer-facing experiences where they support our AI products. We’re looking for someone who can identify the right problems, make thoughtful technical decisions, and take solutions from discovery through implementation, adoption, and ongoing improvement. As you build domain knowledge and establish the AI platform foundation, we’d also like you to grow into contributing directly to AllSpice’s core product alongside the product engineering team. This is an aspirational growth opportunity, not a prerequisite or the role’s initial primary focus.
You will:
- Partner with engineers and product managers to discover workflow bottlenecks, prioritize the highest-impact problems, and own solutions end-to-end—from requirements and architecture to rollout and iteration.
- Own the evaluation and observability layer for our AI products, including automated and human review workflows, regression detection, and comparisons across models, prompts, and pipelines. Make quality, cost, latency, usage, and customer outcomes visible and actionable.
- Build usable internal applications and self-service tools that help engineers and product managers inspect AI results, investigate failures, and provide feedback. Where useful, extend these capabilities into customer-facing experiences.
- Build and maintain scripts, reliable data pipelines, and integrations that connect internal systems, third-party services, LLMs, and Model Context Protocol (MCP) tools, with attention to data quality, schema evolution, and customer data privacy.
- Write clear documentation and communicate findings to both technical and non-technical audiences, including leadership and customers.
- Champion code quality, testing, and reliability across the tooling stack through reviews, mentorship, and thoughtful design.
Example Projects
- Build an internal evaluation workspace for DRCY, our AI design review product, that captures run configurations, inputs, outputs, and telemetry; compares model and prompt changes; and tracks quality, false positives, cost, and latency over time.
- Develop review workflows that let engineers and product managers inspect AI-generated findings, apply scoring rubrics, override automated scores, and investigate regressions—with opportunities to surface relevant insights and feedback workflows to customers.
- Create and maintain data pipelines that aggregate evaluation results, customer feedback, and telemetry into a unified analytics layer.
- Build scripting tools and automations to streamline the Gen AI team's development and testing workflows (e.g., batch evaluation runs, report generation).
- Design and implement RAG-based information repositories and tooling to capture component data and domain knowledge for use by our suite of AI products.
- Integrate with CI/CD systems (GitHub Actions) to surface AI insights directly in engineering workflows.
- Partner with infrastructure to measure cache effectiveness, usage, and cost, and use those insights to improve the reliability and efficiency of AI workflows.
- As an aspirational next step, contribute directly to core AllSpice product features—for example, integrating AI review findings and feedback into existing engineering workflows—in partnership with the product engineering team.
OUR STACK
- Languages: Python, TypeScript/JavaScript, SQL
- Analytics & Data: SQL databases (Postgres), Jupyter Notebooks, business intelligence/analytics tools
- AI/LLM: Langchain, Pydantic AI, Langfuse
- Web: Vue/TypeScript front-end, common web architectures and APIs
- Infrastructure: GitHub Actions for CI/CD, Docker Swarm & Terraform, AWS
- Our Hub application is a soft fork of Gitea + Go [server-side] + Vue/TypeScript Front-end
BASIC QUALIFICATIONS
Our ideal candidate should have the following:
- 4+ years of software engineering experience with a focus on tooling, data platforms, or full-stack web development, with demonstrated senior-level ownership of systems or products that other people depend on.
- Strong SQL skills and experience designing data pipelines and storage schemas, handling data quality and schema evolution, and using data/analytics tools (e.g., Jupyter, Metabase, Looker, or similar BI platforms).
- Proficiency in Python scripting and automation for data pipelines, integrations, and internal tools.
- Experience building web applications or customer-facing tools using modern frameworks (e.g., Vue, React, TypeScript).
- Practical experience shipping or maintaining LLM-enabled systems and building infrastructure around them, such as evaluation pipelines, observability, or integrations. You understand non-determinism, quality and reliability challenges, and tradeoffs across cost, latency, and model performance.
- Excellent communication skills — you can translate technical findings into clear insights for engineers, product managers, and customers alike.
- A customer-first mindset: you think about the end-user experience and proactively seek feedback to improve the tools you build.
- Bachelor's degree or higher in a technology-related field, or equivalent practical experience.
- Project management skills with the ability to lead and collaborate with varied stakeholders to move projects forward.
- Comfort with ambiguity and autonomy: you independently identify problems, propose solutions, make pragmatic build-vs.-buy and architectural decisions, and bring stakeholders along in a fast-moving environment.
PREFERRED QUALIFICATIONS
(Preferred) Availability to work out of our flex offices in San Francisco or Boston on a hybrid basis (2–3 times/week), but we are flexible for the right candidate.
RELEVANT SKILLS
You don't necessarily have to be proficient in all of these, but the more you know, the better:
- Python, TypeScript, SQL
- Business analytics and data visualization tools
- Langchain, Pydantic AI, and LLM evaluation frameworks
- GitHub Actions development and CI/CD
- Common web architectures, APIs, and front-end frameworks (Vue, React)
- Monitoring and observability tools (e.g., Langfuse, DataDog, Grafana)
- Project management and stakeholder communication
BENEFITS
- Supportive and smart colleagues, flexible work, opportunity to make a big impact, competitive salary & equity, health, dental, vision, generous PTO, home office stipend.
COMPENSATION RANGE
$160K - $190K
See all 14,471+ Llm Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Llm Engineer roles.
Get Access To All JobsTips for Finding Visa Sponsorship as a Llm Engineer
Align your degree to LCA job descriptions
Employers file LCAs with a specific job title and degree requirement. If your degree is in mathematics or linguistics rather than computer science, document how your coursework maps directly to LLM engineering duties before interviews start.
Search employer LCA history on Migrate Mate
Filter for employers with verified LCA filing history in machine learning and AI roles. Companies already paying prevailing wage for similar positions move faster through the H-1B petition process than first-time sponsors.
Target companies with cap-exempt H-1B eligibility
AI research labs affiliated with universities and certain nonprofits file cap-exempt H-1B petitions, bypassing the annual lottery entirely. These employers can hire you on H-1B status at any point in the year without waiting for a selection round.
Use OFLC Wage Search to verify your offer
LLM engineering roles span multiple wage levels depending on autonomy and complexity. Pull the prevailing wage for your specific job zone and location before accepting an offer so you can confirm your employer's LCA wage tier is accurate.
Document model deployment work for specialty occupation
USCIS scrutinizes whether a role genuinely requires a bachelor's in a directly related field. Keep records of your work on fine-tuning pipelines, retrieval-augmented generation systems, and production inference infrastructure to support the specialty occupation argument in an RFE.
Confirm STEM OPT employer enrollment before signing
Your employer must be enrolled in E-Verify before your STEM OPT extension is approved. Ask HR to confirm active E-Verify participation during offer negotiations, not after you've already accepted and started the I-765 extension process.
Frequently Asked Questions
Does an LLM engineer role qualify as a specialty occupation for H-1B purposes?
Yes, in most cases. LLM engineering requires at least a bachelor's degree in computer science, mathematics, or a closely related field, which satisfies USCIS's specialty occupation definition. The key risk is a role description that's too broad. If your job posting mentions general software tasks alongside model work, work with your employer to tighten the description so it reflects the theoretical and technical depth the role actually demands.
Which visa categories realistically cover LLM engineer positions?
H-1B is the primary path for long-term authorization, with an initial three-year status extendable to six. F-1 students can work up to 12 months on OPT, then an additional 24 months on STEM OPT if the role ties directly to a STEM-designated degree. Australian nationals can pursue the E-3 visa, which has no lottery and renews every two years. TN visa status does not cover LLM engineering roles, as the USMCA profession list doesn't include this occupation.
How do I find employers actively sponsoring LLM engineer visas?
Migrate Mate shows employers with verified LCA filing history in AI and machine learning roles, so you can focus on companies already navigating the sponsorship process rather than educating a first-time sponsor. Prioritizing employers with recent filing activity in your city and seniority level shortens the path from offer to petition filing.
Can I use STEM OPT for an LLM engineer role if my degree is in linguistics or mathematics?
Yes, provided your degree program carries a STEM-designated CIP code. Computational linguistics and applied mathematics programs often qualify. Your Designated School Official confirms whether your specific program is on the STEM list. The role itself must also relate directly to your degree field, so document the technical overlap between your coursework and your LLM engineering duties in your Form I-983 training plan.
What happens to my H-1B status if my AI startup sponsor loses funding mid-petition?
If the employer withdraws the petition before USCIS approves it, your H-1B petition is terminated and you revert to your current status. If you're already in H-1B status and the company folds, you have a 60-day grace period to find a new employer and have a new petition filed. Under H-1B portability rules, you can start work with the new employer once the new petition is filed, with no additional waiting period.
What is the prevailing wage requirement for sponsored Llm Engineer jobs?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.