💫 Deasie provides data governance to ensure LLMs perform reliably

Our mission is to ensure that language model applications in the enterprise only run on safe, relevant & high-quality data (read our article: https://techbullion.com/why-enterprise-chatbots-are-failing-bridging-the-data-governance-gap/) for more info). Deasie is a platform built for the world's leading enterprises.

Deasie was part of the summer 2023 batch of Y Combinator and closed a $3M seed round in Sep 2023, with investors including General Catalyst & RTP Global.

Deasie's founding team are from McKinsey, QuantumBlack & Amazon, and previously led the build of McKinsey's flagship ML data quality product. The team has educational backgrounds from MIT, the University of Cambridge & the National University of Singapore.

💫 Founding Engineer (Full-Stack)

We are recruiting our first engineering hire to join our founding team of 3 (in New York) to build the future of LLM infrastructure in the enterprise.

1% - 2% equity ownership $120k - $180k salary (dependent on experience & equity selection)

About the role … As Deasie's first hire, you will become a foundational pillar to all of Deasie's technology and play a critical role in shaping the future of the company. You will work hand-in-hand with Deasie's founders and will be fully empowered to design and build core components of Deasie's software product, from conception to deployment. You will provide technical support in early customer deployments and will play a critical role in building out and leading a world-class engineering function over the months and years ahead.

Note: This is a full-time, on-site position in New York and we do not support visa applications. Applicants who do not meet these requirements will not be taken into consideration.

🔑 Key responsibilities …

• Developing core technology: You will drive our innovation through design, build and iteration of new product features, and help define key processes that enable fast build, launch and scaling of the product.
• Defining product roadmap: You will work closely with our founding team and engage directly with customers to gather feedback and refine the technical vision for Deasie.
• Grow as a knowledge leader: You will stay at the forefront of developments in LLM capabilities and relevant technical domains (though research, reading & experimentation).
• Build an engineering function: You will play a critical role in recruiting new developers and have the opportunity to build and lead your own world-class engineering team.

💡 The Deasie mindset …

• You are an entrepreneurial self-starter, comfortable diving into technical problems where you may have limited prior knowledge.
• You enjoy a fast pace of development, iteration & testing (in line with 'lean startup' best practices) and are always looking to learn.
• You are a kind and thoughtful individual, excited to embrace a culture of openness, reflection and learning.

✅ Must haves …

• Bachelor's degree in Computer Science, Engineering or related field, or equivalent training or work experience
• Proven experience as a full-stack engineer, ideally working on B2B SaaS products
• You are able to work in-person in New York
• Experience with Python, end-to-end software development, data structures & algorithms and developing micro-services on cloud (AWS, Azure, etc.)

💚 Nice to have …

• Experience in frontend engineering (ReactJS)
• Experience in developing and maintaining ML models and architecture (Sagemaker, Tensorflow, Azure ML)

😎 Benefits …

• Competitive salary and stock options: 1% - 2% stock option / equity plan; $120k - $180k base salary
• Competition benefits package: Medical, dental, vision insurance, paid time off, company holidays, and 401k matching
• An unrivaled 'day one' opportunity: Deasie was founded in June 2023, went straight into Y Combinator, was one of the fastest companies to close their seed (from tier 1 investors) and are a now on a mission to be the defining data infrastructure in enterprise use of LLMs. You’ll be embedded in the creation of a leading company from day one.
• A culture of learning, openness and optimism: We’re a self-reflective team who speak openly around fears, sources of gratitude and emotional well-being. We prioritize learning, experimentation, and aligning everyone’s work with their strengths to optimize for us all working in ‘flow states'. We value coaching, feedback, and managing our energy levels (e.g., the founders previously finished an 8-week programme, “Lead from love”, based on principles of positive intelligence).
• Thoughtfulness around diversity & inclusion: We promote diversity and provide equal opportunity for all employees with the ambition to build a company that represents a variety of backgrounds, perspectives, and skills.
• In-person collaboration: We believe that our best work happens when we are in the same room, and are thus building an in-person company (New York), with some flexibility for remote working & travel.

Today, most enterprises fail to take their LLM use cases past the 'proof of concept phase'. One of the main challenges is that LLMs simply lack the contextual knowledge required to reliably sift through thousands of documents and consistently retrieve the correct piece of data.

The core technological functionality of Deasie is the auto-creation of metadata relating to both the content and safety of all documents, for which a combination of LLMs and traditional ML models are used. Our metadata tagging ranges from: What document version is this ... to... is this data covered under an NDA ... to ... take all of the types of coverage included in this insurance document...

Through creating this metadata and feeding it into the LLM via the Deasie Index, the LLM accuracy can be enhanced significantly.