Lead Engineer, Fintech

Location: Denver,Colorado,United States

tl;dr - Credit Pulse is hiring a Lead Engineer (Remote, US) to join and build the future of commercial credit risk management. With 6+ pilot customers including multiple $1B+ revenue companies, we’re well-positioned to solve pain points for credit teams at launch.

With increasing interest rates, businesses extending credit to customers are seeing more frequent late payments and insolvencies. Since most B2B transactions rely on trade credit, even minor increases in late payments and bankruptcies can have a massive impact on a company's bottom line. Credit Pulse is working to transform how enterprise customers extend and monitor credit with small/medium-sized customers. 

Credit Pulse aims to revolutionize how enterprises evaluate and monitor credit for small to medium-sized customers by leveraging diverse data sources. By providing real-time updates on over 30 data points, the platform enables companies to make informed credit decisions and address potential issues well in advance. With Credit Pulse, companies can accelerate customer onboarding, reduce bad debt by 20%, and continuously monitor risk. SMBs benefit from getting trade credit and establishing stronger trust with their vendors.

The Founder: 

Jordan Esbin is the Founder/CEO of Credit Pulse and is working with Forum Venture Studio. He has deep experience as a previous startup Founder/CEO, Chief Product Officer, and risk/compliance consultant. Jordan previously led Developer Ecosystem Product Strategy at a Fortune 200 FinTech, building a new platform business with 200 API products across Banking, Capital Markets, and Payments businesses.

Backed by Forum Ventures:

Forum Ventures® is the leading early-stage fund, program, and community for B2B SaaS startups based in New York, San Francisco, Toronto, and remote.  Credit Pulse works with a team of ambitious humans who are former Founders and startup operators to build the best B2B SaaS businesses in the world, from 0 to 1.

As the Lead Engineer, you'll be at the forefront of shaping and building the product as a hands-on technical builder with the opportunity to build and lead a team down the road. This is a founding employee opportunity.

The Why:

Our company is founded on three core beliefs:

1. Need: Trade credit is the bedrock on which retail, construction, and manufacturing industries operate. With increases in late payments and defaults, if the problem is not solved, it could be existential for many businesses. The current underlying tools used for credit risk assessment with SMBs are deeply flawed today. 

2. Tools: So much data exists today that holds predictive value for risk assessment, but currently that data is manually used. We're leveraging this data for better decision-making and pairing it with an intuitive UX.

3. Value creation: By automating credit decisions, and providing real-time monitoring, credit managers can focus on the highest priority areas. The business results are faster customer onboarding (~60%) and significant reductions in bad debt (20%). 

What We Are Looking For:

• Strong technical background with hands-on experience in full-stack software development

• You're well-versed in a modern tech stack, and have expert fluency in the following: JavaScript (Node.js, Next.js, etc.), PostgreSQL, AWS

• Early-stage experience building AI/ML products, or other data-centric products

• Strong product mindset with a passion for delivering customer value

• Startup agility and the ability to work in a fast-paced, dynamic environment

• Proven technical understanding to make wise choices and take smart risks  
  
  

What You Are Looking For:
You are excited by the energy, focus, and white space of an early-stage startup. You want to own the engineering stack end-to-end, and architect and build the core platform and integrations that enable our mission.

You find any of the below questions intriguing and challenging:

• How can we use data, automation, and AI to expedite and streamline the current clunky experience of credit risk assessment?

• How can we ensure our platform is easily extensible for future use cases for credit teams to predict and make decisions based on data?

• How can we design our