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Job Description
Job Description
LandingAI is building the infrastructure to make the world’s documents computable. We are an AI-native company transforming PDFs, PowerPoints, JPGs and other unstructured or semi-structured documents and images into structured data that software can understand and act on. Our focus is on the hardest document understanding problems with complex layouts, tables, images, handwriting, charts, photographs and mixed modalities.
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.About the RoleKey Responsibilities
About LandingAI
LandingAI is building the infrastructure to make the world’s documents computable. We are an AI-native company transforming PDFs, PowerPoints, JPGs and other unstructured or semi-structured documents and images into structured data that software can understand and act on. Our focus is on the hardest document understanding problems with complex layouts, tables, images, handwriting, charts, photographs and mixed modalities.
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.
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.
We are looking for a passionate Applied AI Engineer with strong expertise in document processing, LLMs, NLP, and multimodal AI. This role sits at the intersection of engineering, product, customer success, and sales, contributing both to technical innovation and to strategic, customer-facing engagements.
You'll join a team that blends cutting-edge AI research with the grit and speed of a fast-moving startup. As an Applied AI Engineer, you will design and implement state-of-the-art document AI solutions, lead pre-sales technical efforts, and ensure successful deployments that drive measurable business outcomes for customers. You’ll work cross-functionally with product, engineering, GTM, and partners to help shape the future of the Agentic Document Extraction platform.
Take ownership of LandingAI's pre-sales technical engagements and help develop technical champions at prospects, customers, and partners.
Engage directly with customers to understand their business challenges and technical needs; designing custom demos and POCs leveraging Agentic Document Extraction.
Lead client presentations, whiteboard sessions, and technical workshops, clearly communicating the value, differentiators, and capabilities of Agentic Document Extraction compared to hyperscaler tools or competitors.
Lead the design, development, and deployment of document AI and multimodal pipelines (OCR, LLM-based reasoning, extraction validation, workflow integration).
Deploy models and connectors across Snowflake, AWS, and enterprise VPCs, using containerization (Docker/Kubernetes) and APIs to ensure scalability and security.
Collaborate with sales to articulate technical and business value, supporting executive briefings, proposals, and ROI analyses.
Provide structured customer feedback to Product and Engineering, shaping the Product roadmap.
Partner with ISVs, OEMs, and SIs to extend ADE into verticalized solutions (e.g., invoice reconciliation, legal contract parsing, financial reporting).
Stay current on the latest in LLMs, agentic AI, and document p
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