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AI FundAI FundMountain View, CA

Forward Deployed AI Engineer

Forward Deployed AI Engineer building and deploying custom document AI, multimodal, and agentic LLM solutions for pre-sales POCs, customer deployments, and integrations with Snowflake/AWS. Requires 5+ years in customer-facing AI/ML (especially document processing), strong Python, communication, and enterprise sales support skills.

175k – 225k
On-site5+ YOESolutions Architecture

About the role

Key Responsibilities

  • Take ownership of pre-sales technical engagements and develop technical champions at prospects, customers, and partners.
  • Engage directly with customers to understand business challenges and technical needs; design 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

  • 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 and to build apps and tools to automate recurring internal work.
  • Hands-on experience with Cloud computing (AWS, GCP, Azure) and enterprise VPC deployments.
  • 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.

Skills

PythonLLMsNLPMultimodal AiDocument ProcessingOcrRAGAWSSnowflakeDockerKubernetesClaude CliTensorFlowPyTorch
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