Staff Software Engineer

Cobalt Identity Systems • New York City, NY

10d • Onsite

About The Position

Cobalt ID is building the business identity infrastructure for the financial internet. While others focus on consumers, we separate real companies from synthetic ones. With AI accelerating fraud rings and shell companies at global scale, distinguishing a legitimate business from a sophisticated fraudster is now one of the hardest problems in fintech. We’re mapping 100M+ businesses and counting to expose hidden financial crime networks and ensure real businesses are never left out of the financial ecosystem.

As a Staff Engineer, you'll own the technical vision and architecture of the system. You'll make foundational decisions about how we model entities at massive scale, how we fuse messy data sources into a coherent graph, and how we build the inference layers for fraud intelligence. This isn't a role where you execute on someone else's spec. You'll define what we build and how it works. This is a role with clear leadership opportunity within the company. We're looking for someone who combines deep hands-on engineering ability with the instincts of someone who has led teams or organizations before, and who chose to stay close to the code because that's where they do their best work. You'll set the engineering quality bar, mentor other engineers, and shape how we scale the team and our systems together. The problems are genuinely hard and mostly unsolved by the industry. Similar infrastructure powers leading social media platforms, search engines, and data fusion platforms, but hasn't yet been applied to this problem. If you've been looking for a role where your architectural decisions define an entirely new category of infrastructure, this is it.

Requirements

• Significant experience building production backend systems (we care more about skill and impact than years alone)
• Experience with large-scale data processing infrastructure or distributed systems
• Strong architectural instincts—you have opinions on how systems should scale, but hold them loosely
• Comfort with ambiguity and fast iteration in an early-stage environment
• You want to be close to the problem and the customer, not siloed from product decisions

Nice To Haves

• Background in fintech, fraud detection, or identity systems
• Experience with graph databases, entity resolution, or network analysis at scale
• Experience with ML systems in production, particularly models applied to structured or relational data
• Familiarity with data fusion from messy, heterogeneous real-world sources
• You've built or scaled a platform that had to process tens of millions of entities with complex relationships between them
• Previous experience in engineering management or technical leadership, with a preference for building hands-on

Responsibilities

• Define the long-term technical architecture for a knowledge graph platform operating at massive scale
• Make critical infrastructure decisions (data modeling, system design, build-vs-buy) that will define how this platform scales for the next several years
• Design and build core systems spanning graph storage, entity resolution, inference, and production data pipelines
• Set the engineering quality bar and pioneer AI-powered development processes: code review, system reliability, testing practices, and technical standards for the team
• Ship to production constantly - we're a small team and everything you build matters
• Work directly with founders, customers, and financial institutions to translate hard domain problems into technical solutions
• Shape hiring and team growth as we scale from a small team to a larger engineering organization

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed