AIFund

<div>
<p><strong>Who We Are</strong></p>
<p>AI is the new electricity: Just as electricity transformed numerous industries starting 100 years ago, AI is now poised to do the same.</p>
<p>AI Fund is a venture studio founded by Dr. Andrew Ng in 2017. Our portfolio companies use AI technology to build applications across numerous industry sectors. The AI Fund team combines their experiences as AI pioneers, entrepreneurs, venture capitalists, investors, and operators. We are backed by a $390-million dollar fund from top-tier global corporations and VC firms.</p>
<p>Our purpose is to build AI companies that move humanity forward</p>
<p><strong>What We're Looking For</strong></p>
<p>We are seeking an AI engineer with architecture judgment, product instincts, and fluency across the modern AI application stack.</p>
<p>You should be able to decompose AI products into composable building blocks: model selection, prompting, tool use, retrieval, structured outputs, memory and state, workflow orchestration, planning, reflection, evaluation, observability, and safety controls. You should understand the reason each component belongs in a system, the tradeoffs it introduces, and the evidence needed to know whether it is working.</p>
<p>You start with the simplest design that can answer the open question about an idea, and tighten the architecture only as evidence justifies it.</p>
<p>You follow where AI is heading and ground engineering decisions in product goals, user behavior, the data available for the problem, system constraints, and measured performance. You will collaborate closely with product thinkers, designers, AI experts, and engineers to validate or falsify venture ideas through functional prototypes.</p>
</div>
<h2>What You Will Do:</h2><div>

<li>Build full-stack AI prototypes that pressure-test venture ideas before founder or entrepreneur-in-residence handoff.</li>
<li>Design AI systems from composable building blocks and make the tradeoffs visible to product and engineering partners.</li>
<li>Choose retrieval and context strategies that fit the data and task, from structured queries and hybrid search to reranking, graph traversal, and long-context or human-curated context.</li>
<li>Build agentic and workflow-based systems with clear control flow, bounded autonomy, useful tool interfaces, state management, recovery paths, and human review where appropriate.</li>
<li>Make architecture and platform choices that fit the stage of an idea, keeping prototypes cheap to change while leaving a credible path to production if the idea validates.</li>
<li>Build and integrate APIs, databases, third-party services, internal tools, and cloud infrastructure.</li>
<li>Define evaluation loops for AI behavior, including task success, retrieval quality, factuality, tool-call correctness, grounding, safety, latency, cost, and user-perceived quality.</li>
<li>Use error analysis to decide whether to improve prompts, data, retrieval, tools, orchestration, model choice, UX, or product scope.</li>
<li>Collaborate cross-functionally with product, design, and AI experts to create, test, and iterate on new concepts using direct user feedback.</li>
<li>Present build results to potential entrepreneurs-in-residence and founders: what worked, what failed, what they need to know to decide next steps.</li>
<li>Direct frontier coding agents to turn clear product and technical intent into working software, while owning the architecture, review, debugging, and quality bar.</li>
<li>Identify and troubleshoot issues across the full stack, including frontend, backend, AI orchestration, data pipelines, deployment, and production behavior.</li>
<li>Contribute to better development processes, reusable engineering practices, and shared technical judgment across the team.</li>

</div>
<h2>What You Must Bring:</h2><div>

<li>3+ years of software engineering experience, including end-to-end ownership of at least one production AI application architecture spanning UI, backend, data, models, tools, and evaluation.</li>
<li>Demonstrated experience building applications that use large language models, multimodal models, or other modern AI capabilities in product workflows.</li>
<li>Strong technical fluency across frontend, backend, APIs, databases, and cloud deployment, with enough depth to review, debug, and steer implementation.</li>
<li>Expert ability to work with frontier coding agents, including writing precise specs, decomposing work, inspecting generated code, catching architectural mistakes, and deciding when to intervene directly.</li>
<li>Ability to justify retrieval choices against corpus structure, freshness, permissions, latency, precision, recall, and cost.</li>
<li>Experience with SQL and NoSQL data systems, including the ability to model data for application use, retrieval, analytics, and operational reliability.</li>
<li>Strong communication skills and the ability to work collaboratively across disciplines.</li>
<li>Habit of reading papers, model cards, technical postmortems, and production writeups, then folding useful lessons into the next build.</li>

</div>
<h2>Nice To Have:</h2><div>

<li>Experience shipping MVPs, prototypes, or early-stage products under ambiguity.</li>
<li>Experience as a technical lead, architect, founding engineer, or senior builder on AI-driven products.</li>
<li>Contributions to open-source AI, developer tools, evals, retrieval, agents, or applied ML infrastructure.</li>
<li>Interest or experience in product design, product strategy, or company creation.</li>

</div>

AI Engineer

<div>
<div><strong>About LandingAI</strong></div>
<div><br />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.</div>
<div>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.</div>
<div> </div>
<div>Our work is grounded in three core strengths:</div>
<div>
<ul>
<li><strong>Agentic systems built for production.</strong> 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.</li>
</ul>
<ul>
<li><strong>A data-centric mindset. </strong>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.</li>
</ul>
<ul>
<li><strong>A vision-first approach to foundation models.</strong> 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.</li>
</ul>
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.</div>
<div><br /><strong>This is a place for builders.</strong> 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.</div>
</div>
<h2>About the Role</h2><div>
<p>We are looking for a passionate <strong>Applied AI Engineer</strong> with strong expertise in document processing, LLMs, NLP, and multimodal AI. This role sits at the intersection of<strong> engineering, product, customer success, and sales,</strong> contributing both to technical innovation and to strategic, customer-facing engagements.</p>
<p>You'll join a team that blends cutting-edge AI research with the grit and speed of a fast-moving startup. As an <strong>Applied AI Engineer</strong>, 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.</p>
</div>
<h2>Key Responsibilities</h2><div>

<li>
<p><strong>Take ownership</strong> of LandingAI's pre-sales technical engagements and help develop technical champions at prospects, customers, and partners.</p>
</li>
<li>
<p><strong>Engage directly with customers</strong> to understand their business challenges and technical needs; designing custom demos and <strong>POCs</strong> leveraging Agentic Document Extraction.</p>
</li>
<li>
<p><strong>Lead client presentations</strong>, whiteboard sessions, and technical workshops, clearly communicating the value, differentiators, and capabilities of Agentic Document Extraction compared to hyperscaler tools or competitors.</p>
</li>
<li>
<p><strong>Lead the design, development, and deployment</strong> of document AI and <strong>multimodal pipelines</strong> (OCR, LLM-based reasoning, extraction validation, workflow integration).</p>
</li>
<li>
<p><strong>Deploy models</strong> and connectors across <strong>Snowflake, AWS, and enterprise VPCs</strong>, using containerization (Docker/Kubernetes) and APIs to ensure scalability and security.</p>
</li>
<li>
<p><strong>Collaborate with sales</strong> to articulate technical and business value, supporting executive briefings, proposals, and ROI analyses.</p>
</li>
<li>
<p><strong>Provide structured customer feedback</strong> to Product and Engineering, shaping the Product roadmap.</p>
</li>
<li>
<p><strong>Partner with ISVs, OEMs, and SIs</strong> to extend ADE into verticalized solutions (e.g., invoice reconciliation, legal contract parsing, financial reporting).</p>
</li>
<li>
<p><strong>Stay current</strong> on the latest in <strong>LLMs, agentic AI, and document processing frameworks</strong>.</p>
</li>
<li>
<p><strong>Contribute</strong> to white papers, case studies, and technical blogs showcasing art-of-the-possible workflows and customer success stories.</p>
</li>
<li>
<p><strong>Mentor teammates</strong> and foster a culture of excellence in agentic workflows and document AI best practices.</p>
</li>

</div>
<h2>What You’ll Need to Succeed:</h2><div>

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

</div>
<h2>Nice-to-Have</h2><div>

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

</div>
<h2>LandingAI Benefits</h2><div>

<li>
<p><strong>Stock Awards</strong> – We want you to share in our success with equity grants.</p>
</li>
<li>
<p><strong>Comprehensive Healthcare</strong> – Medical, dental, and vision coverage for you and your dependents.*</p>
</li>
<li>
<p><strong>Wellness Stipend</strong> – Support for your health and well-being, whether it’s fitness programs or self-care.*</p>
</li>
<li>
<p><strong>Lifelong Learning </strong>– An education stipend to help you grow and keep learning.</p>
</li>
<li>
<p><strong>Retirement –</strong> We offer a 401k matching plan to help you plan for your future! </p>
</li>

<p>*Benefits may vary based on your country of employment.</p>
</div>

Customer-facing Applied AI Engineer

<div>
<p>LandingAI is building the infrastructure to make the world’s documents computable.</p>
<p>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.</p>
<p>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.</p>
<p><strong>Our work is grounded in three core strengths:</strong></p>
<ul>
<li>
<p><strong>Agentic systems built for production</strong>. 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.</p>
</li>
<li>
<p><strong>A data-centric mindset</strong>. 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.</p>
</li>
<li>
<p><strong>A vision-first approach to foundation models</strong>. 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.</p>
</li>
</ul>
<p>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.</p>
<strong>This is a place for builders. </strong>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.</div>
<h2>Key Responsibilities</h2><div>

<li>
<p><strong>Be a driving force for the team's agentic coding practice </strong>- establishing patterns for spec-driven development, context engineering, and multi-agent orchestration that compound team output.</p>
</li>
<li>
<p><strong>Design, develop, and maintain</strong> AI-powered applications and services, focusing on high availability, performance, and reliability.</p>
</li>
<li>
<p><strong>Work closely with Machine Learning Engineers</strong>, building AI capabilities from early R&amp;D prototyping to scalable operation in multiple production stacks.</p>
</li>
<li>
<p><strong>Build ML services</strong> designed for low-latency or high-throughput, and optimized for high cost efficiency.</p>
</li>
<li>
<p><strong>Lead cross-functional initiatives</strong>, collaborating with Machine Learning Engineers, Product Managers, and other teams to align technical solutions with business needs.</p>
</li>
<li>
<p><strong>Drive innovation</strong> by making strategic technical decisions, setting best practices, and mentoring engineers to elevate the team’s technical bar.</p>
</li>
<li>
<p><strong>Improve ML development process</strong> by enhancing the internal ML platform, facilitating data sourcing, and enabling ML observability for deployed services.</p>
</li>

</div>
<h2>Required Skills</h2><div>

<li>
<p><strong>Fluency with agentic coding tools </strong>(Claude Code, Codex or equivalent). Experience writing effective specs, managing repo context, and reviewing/verifying agent output.</p>
</li>
<li>
<p><strong>5+ years</strong> of experience in software development, with a strong <strong>backend and ML </strong>engineering background.</p>
</li>
<li>
<p>Experience working with <strong>cloud native</strong> technologies (Docker, Kubernetes).</p>
</li>
<li>
<p>Experience working with <strong>cloud platforms</strong> (AWS, GCP, or Azure).</p>
</li>
<li>
<p>Experience with building <strong>ML systems</strong>, from early prototype, to operating at scale in production.</p>
</li>
<li>
<p>Strong <strong>software architecture skills</strong>, with experience designing and scaling distributed systems and cloud-based applications.</p>
</li>
<li>
<p>Experience <strong>mentoring engineers</strong> and contributing to team-wide technical direction.</p>
</li>
<li>
<p><strong>Strong communication </strong>skills, with the ability to translate technical challenges into business impact.</p>
</li>

</div>
<h2>Nice to Have</h2><div>

<li>
<p>Experience with ML frameworks like <strong>pytorch</strong>.</p>
</li>
<li>
<p>Experience with serving ML models and LLMs using frameworks like <strong>vllm</strong>.</p>
</li>
<li>
<p>Experience with <strong>developer-facing products </strong>and building intuitive APIs.</p>
</li>

</div>

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