Senior AI Engineer

KlearNow is building the intelligence layer for global trade and logistics. We turn fragmented, messy data into instant, reliable intelligence, enabling AI to reason and act in high-stakes, real-world environments. We are a small, sharp team operating at the frontier, and we are looking for builders who want to define the technical foundation from the ground up.

Role Overview

As a Senior AI Engineer on our Applied AI team, you will design and deploy production-grade agentic AI systems that transform real-world workflows at scale. This role is ideal for someone who thrives on ownership, is energized by ambiguity, and wants to ship consequential systems, not just run experiments. You will own end-to-end AI pipelines from data ingestion through retrieval, orchestration, and output, while also shaping product direction and engineering culture.

What You’ll Do

• Design and build multi-agent systems that reason across messy, real-world data


• Own end-to-end AI pipelines — data → retrieval → orchestration → output


• Develop evaluation frameworks, benchmarks, and quality loops to ensure reliability


• Build and scale data ingestion and retrieval infrastructure


• Integrate LLMs with enterprise data, tools, and workflows using frameworks such as:
  
  
  
  • Agno, LangChain, LlamaIndex, and Semantic Kernel
  
  
  • Claude Code, Cursor, and AugmentCode for enterprise agent deployment
  
  


• Ship full-stack product features in close collaboration with end users


• Help define technical architecture, product direction, and engineering culture


• Write clear, well-structured Python and TypeScript code for production ML systems

What We Are Looking For

• 4+ years of hands-on software engineering experience; startup experience strongly preferred


• Proven track record shipping production-grade AI systems, not just prototypes


• Strong hands-on experience with:
  
  
  
  • Agent architectures, LLM systems, and RAG pipelines
  
  
  • Retrieval, grounding, and orchestration techniques
  
  
  • Python (strong proficiency) and TypeScript (working knowledge)
  
  


• 4+ years of infrastructure experience (cloud services, distributed systems)


• 4+ years working with containerization tools such as Docker and Kubernetes


• 2+ years of experience building with Large Language Models (LLMs) in production


• Full-stack ownership mindset — comfortable operating across the entire system


• Strong data instincts and experience working with messy, real-world datasets


• Must be authorized to work in the United States (no visa sponsorship available)


• Ability to commute to the San Jose, CA office (Hybrid Schedule)

Nice to Have

• Experience with evals frameworks and AI quality measurement


• Background in AI infrastructure or distributed systems


• Exposure to automotive, logistics, or other physical-world domains


• MLOps / DevOps experience; CI/CD pipelines, Docker, Kubernetes


• Former founder or early employee at a startup

Why This Role

• Define the core AI systems of the company from the ground up


• Work on problems where AI meets the physical world at scale


• High ownership, high impact, your work ships immediately


• Small, sharp team with a bias for action and a frontier mindset

Company Benefits

KlearNow offers a competitive compensation package commensurate with experience, including:

• Comprehensive medical, dental, and vision insurance


• Equity participation


• Flexible time off


• Collaborative, hybrid in-office environment in our San Jose, CA headquarters


• The US salary range for this position is $187k to $215k in the San Jose Bay Area, California

$187,000 - $215,000 a year

KlearNow is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.