Applied AI Engineer

Key Responsibilities

• 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 processing frameworks.
• Contribute to white papers, case studies, and technical blogs showcasing art-of-the-possible workflows and customer success stories.
• Mentor teammates and foster a culture of excellence in agentic workflows and document AI best practices.

Requirements

• Be based in the San Francisco Bay Area — and able to work in a hybrid/in-office environment in Mountain View.
• Bachelor's or Master's degree in Computer Science, Engineering, or quantitative field, with a strong focus on ML/AI (LLMs, NLP, multimodal AI).
• 5+ years of experience designing AI/ML solutions, with a proven track record in document processing, NLP, or LLM-driven workflows in a pre-sales or customer-facing role.
• 2+ years of experience with cloud data platforms, preferably Snowflake.
• Strong Python skills to guide coding agents and debug AI-written code.
• Ability to use Claude CLI to develop prototype pipelines for customers. Ability to use Claude CLI to build apps and tools to automate recurring internal work.
• Hands-on experience with Cloud computing (AWS, GCP, Azure) and enterprise VPC deployments in these environments.
• Demonstrated understanding of enterprise sales (MEDDIC) and experience supporting sales teams in technical deal cycles.
• Outstanding communication skills; able to explain complex AI workflows (RAG, schema validation, grounding) to both technical and business stakeholders.
• Strong problem-solving skills with a passion for applied AI and customer impact.
• Self-directed and able to manage multiple projects in a dynamic environment.

Nice-to-Haves

• Prior work with OCR, NLP, and multimodal AI for unstructured documents (PDFs, scanned images, photographed documents).
• Deep understanding of LLMs, RAG systems, schema-based extraction, and agentic AI frameworks.
• Familiarity with document AI competitors (e.g., Reducto, LlamaParse, Instabase, Hyperscaler Doc AI, KVP extraction systems).
• Programming languages other than Python primarily JavaScript or C#.
• Deep understanding of ML algorithms and deep learning frameworks (TensorFlow, PyTorch), including computer vision techniques (image recognition, OCR, object detection, segmentation).
• Banking, Insurance, Healthcare or Legal industry experience.