Nxt Level
AI Engineer
Skills
11 days ago
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Important information
Contract type:
Permanent
Salary:
$150,000 – $300,000 / year
Location:
San Francisco, CA, USA
Work mode:
Onsite
Published on:
15 October 2026
What they need
Applied AI Engineer
Location: Palo Alto, California
Employment Type: Full-time
Compensation: $150,000–$300,000 base salary
Focus: Applied AI, Backend Engineering, Multimodal Data, LLMs, AI Infrastructure
About Our Client
Our client is building AI systems that help manufacturers make better decisions and improve execution on the factory floor.
Their platform learns from real-world manufacturing environments, turning complex operational data into actionable intelligence. Rather than building another AI application that lives inside a browser, they're developing technology that directly influences how the physical world operates.
The company is a well-funded, early-stage startup with active design partners and a growing waitlist of manufacturers. Its leadership team brings experience from Stanford, BCG, Porter, and Mercedes-Benz, with founders who have previously built a unicorn and raised hundreds of millions in venture capital.
About the Role
Our client is hiring an Applied AI Engineer to build production-grade AI systems that transform messy, real-world manufacturing data into reliable intelligence.
This is a backend-heavy engineering role focused on multimodal data pipelines, retrieval and reasoning systems, model evaluation, and production APIs.
You'll own systems end-to-end, from architecture and implementation to deployment, monitoring, and continuous improvement.
The ideal candidate is a strong backend engineer who understands applied AI, enjoys solving complex data problems, and wants to build technology that impacts real-world operations.
What You'll Do
- Design and build backend infrastructure for production AI applications.
- Develop multimodal data ingestion pipelines that process complex manufacturing data.
- Build retrieval, reasoning, and data processing systems that power operational intelligence.
- Design reliable, scalable APIs that connect AI systems to real-world workflows.
- Create evaluation and feedback loops to measure and improve model performance.
- Own system reliability, including logging, monitoring, diagnostics, and error handling.
- Work directly with customers and product teams to translate manufacturing challenges into technical solutions.
- Take ownership of engineering decisions from initial design through production.
What We're Looking For
- Strong backend software engineering experience with expertise in TypeScript.
- Experience designing scalable APIs, data pipelines, and production systems.
- Strong understanding of cloud infrastructure, system architecture, and distributed data workflows.
- Familiarity with applied AI, LLMs, retrieval systems, or machine learning applications.
- Ability to build reliable, observable systems and troubleshoot production issues.
- Experience working with complex, unstructured, or real-world data.
- Strong technical judgment and ability to balance speed, scalability, and reliability.
- Comfortable working independently in an early-stage startup environment.
- High ownership, strong problem-solving skills, and a bias toward shipping.
Bonus Experience
- Experience deploying applied AI or ML systems to production.
- Experience with multimodal AI, RAG, agentic workflows, or model evaluation.
- Experience building data ingestion and processing systems.
- Frontend development experience with React or other modern JavaScript frameworks.
- Experience in manufacturing, industrial automation, robotics, or other physical-world applications.
Why This Opportunity
- Build AI systems that directly impact how physical industries operate.
- Join a well-funded startup with experienced founders and early customer traction.
- Work on challenging problems involving multimodal data, retrieval, reasoning, and production AI.
- Own significant portions of the technical architecture and product.
- Collaborate directly with founders, customers, and a highly technical engineering team.
- Help define how AI moves beyond software interfaces and into real-world decision-making.
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