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
Be 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.
Design, develop, and maintain AI-powered applications and services, focusing on high availability, performance, and reliability.
Work closely with Machine Learning Engineers, building AI capabilities from early R&D prototyping to scalable operation in multiple production stacks.
Build ML services designed for low-latency or high-throughput, and optimized for high cost efficiency.
Lead cross-functional initiatives, collaborating with Machine Learning Engineers, Product Managers, and other teams to align technical solutions with business needs.
Drive innovation by making strategic technical decisions, setting best practices, and mentoring engineers to elevate the team’s technical bar.
Improve ML development process by enhancing the internal ML platform, facilitating data sourcing, and enabling ML observability for deployed services.
Required Skills
Fluency with agentic coding tools (Claude Code, Codex or equivalent). Experience writing effective specs, managing repo context, and reviewing/verifying agent output.
5+ years of experience in software development, with a strong backend and ML engineering background.
Experience working with cloud native technologies (Docker, Kubernetes).
Experience working with cloud platforms (AWS, GCP, or Azure).
Experience with building ML systems, from early prototype, to operating at scale in production.
Strong software architecture skills, with experience designing and scaling distributed systems and cloud-based applications.
Experience mentoring engineers and contributing to team-wide technical direction.
Strong communication skills, with the ability to translate technical challenges into business impact.
Nice to Have
Experience with ML frameworks like pytorch.
Experience with serving ML models and LLMs using frameworks like vllm.
Experience with developer-facing products and building intuitive APIs.
Skills Required
- Fluency with agentic coding tools like Claude Code or Codex
- 5+ years of experience in software development with a strong backend and ML engineering background
- Experience with cloud native technologies (Docker, Kubernetes)
- Experience with cloud platforms (AWS, GCP, or Azure)
- Experience building ML systems from prototype to scale in production
- Strong software architecture skills with experience designing distributed systems
- Experience mentoring engineers and contributing to technical direction
- Strong communication skills to translate technical challenges into business impact
AI Fund Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about AI Fund and has not been reviewed or approved by AI Fund.
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Healthcare Strength — Health coverage is portrayed as strong with great healthcare and dental coverage, plus vision insurance, long-term disability, and life insurance. Feedback suggests this aligns with tech-standard benefits for US roles at a small venture studio.
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Retirement Support — Retirement benefits include a 401(k) plan with employer match for US employees. Feedback suggests this forms part of a competitive total package for fund roles.
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Parental & Family Support — Family support includes fully paid parental leave for applicable roles. Feedback suggests this is a standout benefit for an organization of this size.
AI Fund Insights
What We Do
Who is AI Fund? We are a team of AI pioneers, proven entrepreneurs, seasoned operators, and venture capitalists that collaborates with leading entrepreneurs to solve big challenges using artificial intelligence. Founded in 2017 by Dr. Andrew Ng, AI Fund is backed with $176 million in capital by some of the leading VC firms and investors, including NEA, Sequoia, and Greylock. How Are We Different? We work with entrepreneurs during their startup’s most critical and risky phase, from 0 to 1. At the earliest stages, your company strategy is still being formed, and you’re still on the path to demonstrating your idea’s full potential – this is a reality we understand. This is the period when decisions on product strategy, market fit, and team are most critical, moving fast and fixing parts of your business when you have limited resources is a challenge. We believe the best way to help entrepreneurs is by providing our time, expertise, and resources to help flesh out these key strategic decisions. Making the right decisions at the right time can often make the difference. We are here to improve these dynamics, at a time when the help matters the most. Why Work With AI Fund? Getting a startup from idea to Series A funding is not easy. We’ve been there and understand the challenges you must overcome. Whether you desire limited help and just want access to our unique ecosystems of AI experts and entrepreneurs or you would like our full support, we are interested in the opportunity to help in your success. We are flexible in how we work with companies, but ultimately, we are here to maximize your chance of success and accelerate getting your company to market. We provide the capital, expertise, and resources to accelerate the work required to minimize risks in your startup, help you rise above the noise, and make your company more attractive to new investors.
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