Software Engineer, Applied AI

4 weeks ago

San Francisco, United States HackerWeb Full time

About Us

Fintechs and banks use Greenlite agents to automate workflows like suspicious activity investigations, entity due diligence and regulatory reporting.

We've raised $4.8M led by Greylock, generate significant annual recurring revenue and already serve financial institutions across three continents. We're on a high-growth trajectory and we're looking for people who want to join us on the journey to building a billion-dollar company.

The problem we’re trying to solve

The internet revolutionized the way financial services are distributed, making them more accessible and convenient than ever before. However, this rapid expansion has also led to a new challenge: an overwhelming amount of noise and a scarcity of clear, actionable signals for making sound risk decisions.

Today, teams are faced with the increasing challenge of navigating the complex landscape of compliance and onboarding. Manual due diligence processes are time-consuming and difficult to scale, hindering the ability to efficiently identify and mitigate risks.

How we’re solving this problem

This is where Greenlite comes in. Our mission is to boost the signal amidst the noise, empowering financial institutions to make informed decisions and expand access to financial services for the businesses and individuals who need it most. With the help of large language models, we're transforming the way compliance and onboarding teams operate, enabling them to work smarter, faster, and more effectively.

The Role

As a Software Engineer, Applied AI at Greenlite, you’ll work on building our core agent frameworks, innovating on how LLMs are used by the world's largest enterprises. You'll be testing, deploying, and scaling delightful AI experiences in addition to ensuring that our outputs are extremely high quality. This role is perfect for someone who is obsessed with language models and wants to spend their time becoming an expert in applied AI.

What to expect

Within days:

  • Translate novel LLM capabilities into understandable, intuitive, and performant end-user experiences.
  • Work directly with customers to solve their problems. We need someone who has high empathy and is excited by working side-by-side with financial crime teams to solve critical real world problems.
  • Collaborate with the CEO, CTO, and other founding members to help build out our team.

Within weeks:

  • Build integration and product infrastructure for LLMs. Provide Greenlite agents with the infrastructure, data sources, and tools they need to automate workflows for financial compliance teams.
  • Lead customer calls and the development of new features end-to-end.

Within months:

  • Own the architecture and development of our AI product frameworks. Scale our AI services to reliably serve customers across geographies, tech stacks, and business types.
  • Hire, onboard, and nurture future teammates.

Our tech stack

  • NextJS
  • Node
  • Postgres
  • Typescript

If you, like us, believe that AI can transform the way we work, this role is a great fit for you.

About You

  • Customer curious — You are interested in deeply understanding customer pain points and are motivated to engage with and solve customer problems.
  • Experience building, and being part of, fast-growing B2B software products — You’ve worked on some of the world's best teams where you needed to ship fast and often. Bonus if you’ve built fintech or enterprise software products for large customers.
  • Entrepreneurial drive — You’re able to work without explicit direction and feel intense ownership over the products you create. As a founding member, you’ll be expected to thrive in the ambiguity that comes with an early-stage startup and can get things done without overcomplicating the solution.
  • Strong communicator — As an early-stage startup, there will be lots of changes and ambiguity in the beginning. You should be comfortable sharing your feedback early and often, and you should be comfortable bringing up product ideas frequently.
Compensation
  • $120K to $200K based on experience
  • Generous equity
  • Commuter benefit
  • 401k with match
  • Health, vision, dental
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