LandingAI is building the infrastructure to make the world’s documents computable.
We are an AI-native company transforming unstructured and dark data into trusted, structured, auditable data that software can understand and act on. Our focus is on the hardest document understanding problems: multiple document types, complex layouts, tables, images, handwriting, and mixed modalities within and across workflows.
Founded by Andrew Ng, LandingAI has brought together some of the strongest AI Engineers and Machine Learning Engineers in the industry, with deep expertise in visual AI, agentic systems, foundation models, and production ML infrastructure. We build from the ground up where it matters, move fast with the latest AI coding tools and agentic developer workflows, and invest in the compute and technical environment needed to do exceptional work.
Our work is grounded in three core strengths:
Agentic systems built for production. We have been early builders of agentic AI systems and have applied that work in the real world through Agentic Document Extraction (ADE), our platform for parsing, understanding, and extracting information from complex documents with traceability, control, and production-grade reliability.
A data-centric mindset. We bring a rigorous, practical approach to model quality, edge cases, evaluation, and real customer data, because solving document understanding in production requires far more than strong benchmark performance.
A vision-first approach to foundation models. We build from the ground up where it matters, including specialized document models and agentic systems, because solving real document understanding problems requires more than stitching together generic components.
Since launching Agentic Document Extraction in early 2025, LandingAI has grown quickly by bringing a modern, AI-native approach to a legacy intelligent document processing market ready for disruption.
This is a place for builders. If you want to work on real technical depth, move quickly, take ownership, and help define the future of document intelligence, LandingAI is the place to do it.
Key Responsibilities
Being a driving force for the team's agentic coding practice - establishing patterns for spec-driven development, context engineering, and multi-agent orchestration that compound team output.
Owning and defining architecture for AI-powered applications and services, ensuring scalability, security, and maintainability across teams.
Designing, developing, and deploying backend infrastructure and AI services with a focus on high availability, performance, and reliability.
Leading cross-functional initiatives, collaborating with Machine Learning Engineers, Product Managers, and other teams to align technical solutions with business needs.
Driving innovation by making strategic technical decisions, setting best practices, and mentoring engineers to elevate the team’s technical bar.
Improving developer experience by building internal tooling, streamlining workflows, and optimizing deployment pipelines.
Ensuring seamless data flow, building high-throughput, secure, and scalable data pipelines to support AI model training and deployment.
Championing best practices in software engineering, ensuring high-quality code, rigorous testing, and well-documented design decisions.
Required Skills
5+ years of experience in software development, with a strong backend / full-stack engineering background.
Fluency with agentic coding tools (Claude Code, Codex or equivalent). Experience writing effective specs, managing repo context, and reviewing/verifying agent output.
Expertise in backend development, with proficiency in Python and/or Node.js and modern web frameworks like FastAPI, Flask, Express.js, Next.js
Strong software architecture skills, with experience designing and scaling distributed systems and cloud-based applications.
Hands-on experience with Docker and Kubernetes for containerization and orchestration.
Database expertise, including SQL, NoSQL, and data streaming solutions.
Experience working with cloud platforms such as AWS, GCP, or Azure.
Proficiency in software engineering best practices, including code reviews, unit testing, CI/CD pipelines, and system design.
Experience mentoring engineers and contributing to team-wide technical direction.
Strong communication skills, with the ability to translate technical challenges into business impact.
Proven track record of leading fullstack projects, from early prototypes to production systems.
Nice to Have
Familiarity with Stripe, subscription management.
Exposure to computer vision, LLMs, or multimodal AI applications.
Experience with developer-facing products and building intuitive APIs.
AI Fund Palo Alto, California, USA Office
Palo Alto, CA, United States, 94303
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