AI Engineer

AI Engineer


AI Engineer opportunity in San Mateo, California (remote-friendly) with a confidential employer. This high-growth, late-stage AI infrastructure company seeks AI Field Engineers who can bridge generative AI and enterprise customers. You will turn ambitious GenAI ideas into production systems for some of the world's most sophisticated organizations. Compensation is highly competitive, with a base salary of $175,000-$225,000 plus bonus and equity, pushing on-target earnings to approximately $220,000-$280,000. The role offers remote flexibility across the US and the chance to influence cutting-edge AI-native technology.

Role Snapshot

Company: Confidential Employer


Location: San Mateo, California, USA


Industry: Software


Degree: Not specified


Compensation: 175000



Short Description

AI Engineer opportunity in San Mateo, California (remote-friendly) with a confidential employer. This high-growth, late-stage AI infrastructure company seeks AI Field Engineers who can bridge generative AI and enterprise customers. You will turn ambitious GenAI ideas into production systems for some of the world's most sophisticated organizations. Compensation is highly competitive, with a base salary of $175,000-$225,000 plus bonus and equity, pushing on-target earnings to approximately $220,000-$280,000. The role offers remote flexibility across the US and the chance to influence cutting-edge AI-native technology.

Non-Negotiables

• You must have at least three years of experience in customer-facing AI/ML or infrastructure roles, with a record of owning technical workstreams in enterprise accounts
• You must have shipped real AI/ML production code into customer environments, not just delivered slideware or advisory engagements
• You must have hands-on experience with LLM inference and/or training using open-model frameworks, including modern serving stacks and fine-tuning workflows such as SFT
• You must be strong in Python and comfortable with GPUs, cloud infrastructure (AWS, Azure, or GCP), and container/orchestration tools such as Kubernetes
• You must demonstrate executive-level presence, able to dive deep with engineers and explain trade-offs to senior leadership in the same day
• Your LLM experience must go beyond closed-model APIs and wrapper libraries; exposure to open-model inference or fine-tuning is required
• You cannot come from a purely advisory or research-only background without evidence of shipping production systems

What's In It For You

• You will earn a competitive base salary of $175,000 to $225,000, plus bonus and equity that bring on-target earnings to approximately $220,000 to $280,000
• You will receive meaningful equity in a well-capitalized, rapidly scaling company where ownership can still move the needle
• The role is remote-friendly across the United States, with flexibility for strong candidates to work fully remote and regular travel to marquee enterprise customers
• You will work on AI-native technology at a high-growth company that is shaping the enterprise AI landscape
• Your contributions will have immediate impact, with the opportunity to influence product direction and see your work deployed at scale
• Visa support is available for select categories, including common transfer paths for experienced engineers

Responsibilities

• You will lead technical discovery with enterprise customers, scope proofs of concept, and run load tests to validate model architectures and deployment setups
• You will build end-to-end proofs of concept and production integrations directly inside customer environments, working through infrastructure, security, and compliance constraints to get systems live
• You will advise customers on model selection and fine-tuning strategies, such as SFT, DPO, and RFT, and design evaluation frameworks that take them from experimentation to production at scale
• You will own the technical relationship across complex accounts, identifying champions, managing detractors, and aligning stakeholders to keep deals and deployments moving
• You will feed recurring patterns and customer pain points back into the product and engineering organization as a direct loop from field to roadmap

Preferred Qualifications

• Exposure to advanced fine-tuning techniques such as DPO or RFT is strongly preferred
• Experience working in startup or high-growth environments with rapid iteration cycles and limited structure is a plus
• A track record of collaborating closely with product and engineering teams to translate field learnings into product improvements is highly valued
• Familiarity with multiple cloud platforms (AWS, Azure, GCP) and container orchestration beyond Kubernetes is advantageous
• Strong communication skills and the ability to explain complex technical concepts to non-technical stakeholders are preferred

Role Details & Location

Employment Type: Full Time/Direct Hire


Remote Status: hybrid_remote


Work Experience: 4


Total Openings: 10


Location String: San Mateo, California, USA


ZIP: Not specified



Long Description

Join a well-funded AI infrastructure company as an AI Engineer, where you will work at the intersection of generative AI and real enterprise problems. This is a hands-on role that turns ambitious ideas into live production systems for some of the most advanced organizations in the world. The company is backed by top-tier investors, scaling fast, and offers equity that can significantly impact your financial future.

You will lead technical discovery with enterprise clients, scope and build proofs of concept, and run evaluations to validate the right model architectures. You will design and integrate solutions directly inside customer environments, tackling security and compliance challenges along the way. Your insights will feed directly into the product roadmap, giving you a visible impact on the technology's direction.

If you have a track record of delivering AI/ML into enterprise accounts, deep experience with open-model inference and fine-tuning, and the ability to communicate with both engineers and executives, this is your chance to shape the future of enterprise AI. Apply today to join a confidential employer that is redefining AI infrastructure.