Were building the financial ops platform for construction a $12T global industry run by software built 20-40 years ago much of it on-prem with no APIs and no documentation.
We spent 3 years building the rails to read and write across those systems and we use them to deploy AI for invoicing expenses compliance billing and more.
Were looking for a world-class engineer who loves simplifying complex systems unifying fragmented data and building high-scale backend systems.
Responsibilities
INTERESTING TECHNICAL CHALLENGES:
Unification: were unifying dozens-to-hundreds of fragmented systems under a single standard that we define. Our unification covers data objects data models authentication account-linking UX and features like filters and pagination. When designing any new feature we have to do it in a scalable way. For example when adding filters we have to research each system we support (and plan to support) and create a generic system-agnostic solution.
On-prem: were connecting with many types of on-prem systems (SQL-based DLL-based API-based) many built 20-40 years ago. We provide tremendous value to customers allowing them to interface with these systems in a secure fast reliable way as if theyre modern cloud-based products. We need to support real-time communication and webhooks when they dont exist (e.g. using web-sockets).
Scale & speed: were handling millions of API requests per day and growing daily. For our products that we power with our own API (e.g. Analytics) we need to store and retrieve large amounts of data in an efficient way building elegant caching layers to reduce latency. We ship code daily and iterate quickly based on actual feedback from paying customers (they share tons!).
Operational excellence: were creating a reliable API layer on top of many old systems that dont have APIs. Its like building a skyscraper on quicksand enforced by SLAs. We need to innovate in expanding the depth and breadth of our integrations while simultaneously increasing our development velocity. We need to be very creative in how to continually test our code and integrations creating scalable testing frameworks that can catch edge cases and bugs across 1k endpoints.
Mix of back-end and front-end: were building front-end apps that dog-food our own APIs (e.g. Sync Analytics). This helps us build world-class APIs because we suffer any pain present in our API. Were building both the lego blocks and the higher-level lego models: we see what kinds of APIs our SaaS customers want then also look at the kinds of API niceties we want for our own applications (like a caching layer advanced filtering) and implement a combination of the two.
Variety: without knowing you might assume adding a new integration is low-ambiguity and routine. But each integration we launch is special completely different and posing unique challenges. This requires researching that system and its nuances in great depth before building on top of it. Its part engineering part archaeology.
Requirements
Seniority
1 - 4 years of experience in back-end/full-stack software engineer. Must be able to work independently without much guidance.
Work experience
Startup focused: recent experience at small (Seed to Series B) tech startup. No more than 2yrs at later-stage/public companies.
Updated
Education
Undergrad CS degree - no bootcamps
Top US/CAN school: CS degree from a top 25 undergrad school in US or Canada
Updated
Hard skills
Candidate shouldnot be primarily LLM/AI focusedand give the impression that they mainly want to work on AI given we are not AI-focused
Updated
Familiarity with cloud infrastructure (e.g. AWS)
Updated
Soft skills
Self-motivated high ownership low ego; desire to work on a fast-paced intense fun team. Excited to be our next hire; passion for building a world-class engineering culture
Updated
Miscellaneous
Some indication of excellence:whether that be coming from a top US/CAN school excelling at a reputable startup or having other standout accomplishments
Benefits
Healthcare: we cover 90% of your healthcare costs with several plan options.
401k: we match 100% of your contributions up to 4% of annual salary.
Relocation: sizable relocation bonus for folks currently located outside of the Bay Area.
Gym: on-site gym with Peloton squat rack Tempo Yoga setup and more.
Visa: we sponsor Visas (H1B TN etc.) for candidates who are a good fit!
Commuter benefits: employees can make pre-tax contributions toward commuting costs and well cover the full cost of a Muni pass for those using public transit.
Breakfast & Dinner delivered: breakfast and dinner stipends through DoorDash. Plus a kitchen stocked with coffee snacks drinks and more
Required Skills:
Proficient in Python (bonus for TypeScript and React).Regularly uses AI coding assistants (e.g. Copilot Cursor). Experience building with or deploying LLMs/AI models.
Required Education:
Candidates should hold a CS or equivalent technical undergraduate degree from a U.S. school
AI Talent Now job # ZR97JOBAbout us:Were building the financial ops platform for construction a $12T global industry run by software built 20-40 years ago much of it on-prem with no APIs and no documentation.We spent 3 years building the rails to read and write across those systems and we use them t...
AI Talent Now job # ZR97JOB
About us:
Were building the financial ops platform for construction a $12T global industry run by software built 20-40 years ago much of it on-prem with no APIs and no documentation.
We spent 3 years building the rails to read and write across those systems and we use them to deploy AI for invoicing expenses compliance billing and more.
Were looking for a world-class engineer who loves simplifying complex systems unifying fragmented data and building high-scale backend systems.
Responsibilities
INTERESTING TECHNICAL CHALLENGES:
Unification: were unifying dozens-to-hundreds of fragmented systems under a single standard that we define. Our unification covers data objects data models authentication account-linking UX and features like filters and pagination. When designing any new feature we have to do it in a scalable way. For example when adding filters we have to research each system we support (and plan to support) and create a generic system-agnostic solution.
On-prem: were connecting with many types of on-prem systems (SQL-based DLL-based API-based) many built 20-40 years ago. We provide tremendous value to customers allowing them to interface with these systems in a secure fast reliable way as if theyre modern cloud-based products. We need to support real-time communication and webhooks when they dont exist (e.g. using web-sockets).
Scale & speed: were handling millions of API requests per day and growing daily. For our products that we power with our own API (e.g. Analytics) we need to store and retrieve large amounts of data in an efficient way building elegant caching layers to reduce latency. We ship code daily and iterate quickly based on actual feedback from paying customers (they share tons!).
Operational excellence: were creating a reliable API layer on top of many old systems that dont have APIs. Its like building a skyscraper on quicksand enforced by SLAs. We need to innovate in expanding the depth and breadth of our integrations while simultaneously increasing our development velocity. We need to be very creative in how to continually test our code and integrations creating scalable testing frameworks that can catch edge cases and bugs across 1k endpoints.
Mix of back-end and front-end: were building front-end apps that dog-food our own APIs (e.g. Sync Analytics). This helps us build world-class APIs because we suffer any pain present in our API. Were building both the lego blocks and the higher-level lego models: we see what kinds of APIs our SaaS customers want then also look at the kinds of API niceties we want for our own applications (like a caching layer advanced filtering) and implement a combination of the two.
Variety: without knowing you might assume adding a new integration is low-ambiguity and routine. But each integration we launch is special completely different and posing unique challenges. This requires researching that system and its nuances in great depth before building on top of it. Its part engineering part archaeology.
Requirements
Seniority
1 - 4 years of experience in back-end/full-stack software engineer. Must be able to work independently without much guidance.
Work experience
Startup focused: recent experience at small (Seed to Series B) tech startup. No more than 2yrs at later-stage/public companies.
Updated
Education
Undergrad CS degree - no bootcamps
Top US/CAN school: CS degree from a top 25 undergrad school in US or Canada
Updated
Hard skills
Candidate shouldnot be primarily LLM/AI focusedand give the impression that they mainly want to work on AI given we are not AI-focused
Updated
Familiarity with cloud infrastructure (e.g. AWS)
Updated
Soft skills
Self-motivated high ownership low ego; desire to work on a fast-paced intense fun team. Excited to be our next hire; passion for building a world-class engineering culture
Updated
Miscellaneous
Some indication of excellence:whether that be coming from a top US/CAN school excelling at a reputable startup or having other standout accomplishments
Benefits
Healthcare: we cover 90% of your healthcare costs with several plan options.
401k: we match 100% of your contributions up to 4% of annual salary.
Relocation: sizable relocation bonus for folks currently located outside of the Bay Area.
Gym: on-site gym with Peloton squat rack Tempo Yoga setup and more.
Visa: we sponsor Visas (H1B TN etc.) for candidates who are a good fit!
Commuter benefits: employees can make pre-tax contributions toward commuting costs and well cover the full cost of a Muni pass for those using public transit.
Breakfast & Dinner delivered: breakfast and dinner stipends through DoorDash. Plus a kitchen stocked with coffee snacks drinks and more
Required Skills:
Proficient in Python (bonus for TypeScript and React).Regularly uses AI coding assistants (e.g. Copilot Cursor). Experience building with or deploying LLMs/AI models.
Required Education:
Candidates should hold a CS or equivalent technical undergraduate degree from a U.S. school