Embedding VC Logo

Embedding VC

Solution Engineer

Posted 2 Days Ago
Be an Early Applicant
Hybrid
Mountain View, CA, USA
Entry level
Hybrid
Mountain View, CA, USA
Entry level
Deploy and operate physical AI agents at airports, stadiums, conferences, retail spaces, and other high-profile venues. Build production software using Python or JavaScript/TypeScript, configure hardware and networking equipment, troubleshoot on-site, present demonstrations, and communicate with customers and VIPs. The role also provides field feedback to engineering and product teams while managing code, hardware, customers, and live deployments in a fast-paced startup environment.
The summary above was generated by AI

This Isn't Your Typical Engineering Job

Imagine this: you're backstage at the NFL Super Bowl, making sure a physical AI agent is ready to go live in front of millions — and NFL Commissioner Roger Goodell walks by to check it out. A few weeks later, you're at San Jose International Airport deploying AI alongside Mayor Matt Mahan. Then you're at NVIDIA GTC, the world's biggest AI conference, and you bump into Jensen Huang himself.

That's not a hypothetical. That's what our team actually did.

At LiveX AI, we build physical AI agents — intelligent, embodied systems that interact with people in the real world. Not chatbots on a screen. Real AI that lives in airports, stadiums, conference halls, and beyond. We're looking for a bold, driven Solution Engineer to join our core team full-time and help us deploy these systems on the world stage.

About LiveX AI

LiveX AI is a fast-growing startup headquartered in the San Francisco Bay Area, building the next generation of physical AI agents. Our technology combines advanced large language models, multimodal AI, and purpose-built hardware to create AI experiences that people interact with face-to-face. We're backed by leading investors and trusted by enterprises, cities, and major event organizers worldwide.

What You'll Do

You'll be embedded in our core deployment team — the people who take our AI from the lab to the real world.

  • Ship physical AI agents. Build, test, and deploy AI-powered hardware systems to real venues — airports, stadiums, conference centers, retail spaces. You'll own deployments end to end and see your work in action, not just in a staging environment.

  • Get your hands dirty with hardware. Set up screens, sensors, networking gear, and edge compute devices. Debug on-site. Make AI work in the physical world, where Wi-Fi drops, power flickers, and thousands of people walk by.

  • Write real code. Build software that powers our AI agents — Python, TypeScript, APIs, integrations. Contribute to the same codebase the rest of engineering works in. Your commits go to production.

  • Work the world's biggest stages. Lead and support deployments at marquee events and high-profile locations. Previous team deployments include the NFL Super Bowl, San Jose Airport, and NVIDIA GTC. You could be next.

  • Talk to real humans. Present demos to customers, partners, and VIPs. Explain how our AI works to both technical and non-technical audiences. Your communication skills matter as much as your code.

  • Shape the product. Feed real-world observations back to engineering and product. When you notice something in the field, your input directly influences what we build next.

How We Evaluate Candidates

We hire for the traits that make someone thrive in fast-moving, high-stakes deployments. Every candidate is evaluated on four things:

  • Responsibility & dedication. You take full ownership of your work and follow through. When a deployment is on the line, you do whatever it takes to get it right — and you can be counted on.

  • Speed of learning. Our stack, our hardware, and our customers change fast. You pick up new tools, technologies, and contexts quickly and turn them into results without hand-holding.

  • Multi-tasking capability. You juggle code, hardware, customers, and live events at once — often in the same day — and keep all of them moving without dropping the ball.

  • Communication skills. You explain technical concepts clearly to anyone — a mayor, a CEO, a teammate, or a curious bystander — and you keep the team aligned under pressure.

  • Who You Are

  • Ideally, you've delivered enterprise software at a startup, or run enterprise projects at a consulting firm — you know how to ship for demanding customers and manage delivery end to end.

  • You code. Python, JavaScript/TypeScript, or both. You've built and shipped things that went beyond the spec.

  • You're genuinely excited about AI — not just the hype, but how LLMs, computer vision, and multimodal models actually work under the hood.

  • Hardware doesn't scare you (or it does, but you want to learn anyway). You're willing to carry a monitor, run cables, and troubleshoot on-site.

  • You communicate clearly — to a mayor, a CEO, or a curious bystander at a trade show.

  • You thrive in chaos. Startups are messy. Deployments have surprises. You stay calm, figure it out, and keep going.

  • You're a team player who brings energy, not ego.

Bonus Points

  • Experience with LLM frameworks (LangChain, LlamaIndex), prompt engineering, or RAG pipelines.

  • Familiarity with edge computing, IoT, AV systems, or robotics.

  • Prior startup or hackathon experience where you shipped something under pressure.

  • Background in CS, EE, information systems, or a related technical field.

Why You'll Love This

  • World-stage experiences. Your LinkedIn won't say "updated Jira tickets." It'll say "deployed AI at the Super Bowl."

  • Full-stack, full-real. AI + software + hardware + customer-facing — you'll build a skill set most engineers don't reach until years into their careers.

  • Silicon Valley, front row. You'll work at the center of the physical AI movement, with the connections and momentum that come with it.

  • Mentorship that matters. You'll work directly with founders and senior engineers who want to see you grow — not hand you busywork.

  • Real ownership & growth. Top performers take on more scope fast — leading deployments, owning customers, and shaping the product.

  • Competitive salary, equity, and benefits.

Similar Jobs

18 Days Ago
Easy Apply
Hybrid
San Francisco, CA, USA
Easy Apply
Senior level
Senior level
Fintech • Payments • Financial Services
Own the technical relationship with complex hardware OEM partners. Lead device-level escalations, define technical strategy, align cross-functional teams, improve tooling and automation, and enhance payment experiences on partner devices. Mentor engineers and help develop a scalable hardware partner engineering model. The role requires extensive customer-facing technical expertise, embedded or systems engineering experience, strong communication, strategic judgment, and travel to OEM locations.
Top Skills: AndroidEmbedded SystemsFirmwareHardware
23 Days Ago
In-Office
Sunnyvale, CA, USA
187K-378K Annually
Senior level
187K-378K Annually
Senior level
Artificial Intelligence • Cloud • Information Technology • Consulting
Leads quality engineering for large-scale networking and distributed software solutions. Designs automation frameworks, integrates testing into CI/CD, validates performance, resilience, interoperability, scalability, and recovery, and drives complex root-cause investigations. Partners with customers and cross-functional teams on solution validation, architecture, and operational readiness. Provides technical leadership, mentors engineers, establishes quality practices, and advances automation, observability, reliability, and customer outcomes.
Top Skills: Ai-Assisted Engineering ToolsAutomation FrameworksC++Ci/CdCloud InfrastructureDistributed SystemsEvpnGoIxiaJunosLinuxMplsNetwork Operating SystemsObservability PlatformsPythonRoutingSpirentTcp/IpUnix
3 Days Ago
In-Office or Remote
Menlo Park, CA, USA
165K-217K Annually
Senior level
165K-217K Annually
Senior level
Artificial Intelligence • Big Data • Cloud • Machine Learning • Software • Database • Analytics
Partner with sales teams and customers to solve complex technical problems, demonstrate Snowflake solutions, support enterprise proofs of concept, and close large deals. Present to executive and technical audiences, conduct architectural discovery, build cloud-based machine learning and generative AI solutions, and position Snowflake against competing technologies. Collaborate with channel partners, Product Management, Engineering, and Marketing throughout the sales cycle.
Top Skills: Cloud ComputingData FabricData LakesData MeshData WarehousesDatabasesETLGenerative AiMachine LearningPythonSnowflakeSQL

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account