VP of Engineering (CTO), New Venture: Next-Gen Data Infrastructure Startup

The Opportunity

Over the past few years, more than 30 new state and federal leave laws have emerged in the US. By 2030, employers are expected to spend over $40B annually on employee leave protection. While this shift benefits employees, it has introduced significant operational and data complexity for employers, insurance carriers, and third party administrators.

Leave administration today relies on fragmented systems and brittle integrations. Critical employee events must move accurately between HR systems, payroll providers, benefits platforms, and insurance carriers. Data is often inconsistent, incomplete, or delayed, and when it breaks, the impact is operational, financial, and sometimes regulatory.

We are building the data infrastructure layer between HR systems and insurance carriers. Our platform orchestrates complex data flows, normalizes inconsistent schemas, and enables reliable, auditable data exchange across systems that were never designed to work together.

A core part of our approach is using modern AI primitives such as agents and MCP style servers to simplify systems connectivity, automate process and data discovery, and reduce the manual effort required to integrate complex enterprise systems.

We are an early-stage startup, backed by Diagram Ventures and working directly with insurance carriers as early partners. This is a founding technical leadership role. You will be the first and most senior engineering leader, reporting directly to the co-founder and responsible for building a technical foundation that customers and partners can trust. If the partnership works well and the company scales as expected, this role is intended to evolve into a CTO position over time.

What You’ll Own

You are the single point of accountability for all Technology and Engineering.

Specifically, you will own:

• Define and own the end to end technical architecture and platform foundations
• Write production code in the early stages and set engineering standards
• Hire, grow, and manage the engineering team over time
• Establish pragmatic engineering processes that scale with the company
• Design, build, and operate data ingestion, ETL, normalization, and reconciliation pipelines
• Own data correctness, auditability, observability, and system reliability
• Build and operate agent based systems to simplify integrations and automate discovery workflows
• Design MCP style services to enable scalable, AI assisted systems connectivity

The Hard Problems You will Work On

• Normalizing inconsistent HRIS, payroll, and benefits data at scale across many schema variants
• Designing resilient ETL pipelines that tolerate schema drift, partial failures, and undocumented system behavior
• Using agents to automate system exploration, schema discovery, and integration setup
• Applying AI driven approaches to process discovery, exception handling, and data reconciliation
• Balancing deterministic infrastructure with probabilistic AI systems in high trust and regulated workflows
• Building systems where humans remain in the loop when accuracy, compliance, or risk thresholds require it

What Success Looks Like in 12 Months

• Production grade data pipelines live with multiple external partners
• Clear and durable architecture decisions in place
• A strong initial engineering team operating effectively
• High confidence in data correctness, traceability, and system reliability
• A foundation that supports regulatory and customer scale

Who This Is For

You are likely a strong fit if you:

• Have owned technology end to end in an early stage or scaling company
• Have deep experience with data platforms, ETL pipelines, and integration heavy systems
• Enjoy staying hands on while building and leading a team
• Are comfortable making decisions with ambiguity and real consequences
• Are excited to apply modern AI techniques to real infrastructure problems

What You Get

• Meaningful equity aligned with founding level impact
• Direct reporting line to the co founder and real influence on company direction
• Full ownership of the company’s technical foundation
• The chance to build long lived infrastructure at the edge of modern AI and data systems
• Support from Diagram Ventures, including early partners, capital, and reduced startup risk

About Diagram

Diagram’s mission is to build companies that solve meaningful problems. We partner with top entrepreneurs, match them with vetted ideas, and provide capital, resources, and an ecosystem to accelerate success.

Since 2016, Diagram has raised $400M+, launched/invested in 25+ companies in Fintech and ClimateTech, and cultivated an ecosystem of 200+ angel investors and a global partner network. Diagram is part of Sagard, a global alternative investment platform with $25B+ AUM.