You have scaled engineering teams building mission-critical fintech platforms.
You know how to ship fast without creating technical debt disasters.
You can translate product vision into systems, teams, and execution.
You thrive where AI, data, and real-world financial impact intersect.
If you have only operated in slow-moving enterprises, this will feel intense.
You will own all of engineering at Reflexivity.
This role exists because the platform is scaling in users, data, and technical ambition.
You will lead multiple squads across AI, backend, data systems, and infrastructure.
Your job is to build a world-class engineering organization that ships reliably.
Set technical strategy across AI, data, backend, and platform systems
Scale and lead high-performing engineering teams
Own delivery quality, system reliability, and long-term architecture
Partner closely with founders and product leadership
Make build vs buy decisions with speed and clarity
Create hiring standards that attract senior, high-signal engineers
Ensure AI systems are production-grade, not experimental
After 3 months
You understand every major system, team dynamic, and delivery bottleneck.
After 6 months
Engineering velocity improves while system stability increases.
After 12 months
Reflexivity runs on a scalable, resilient platform with a strong engineering culture.
10 plus years in engineering leadership roles
Significant experience in fintech or investment platforms
Built and scaled data-heavy, AI-powered systems in production
Led teams through rapid growth stages
Strong technical background in modern backend architectures
Comfortable diving into code and architecture when needed
Proven hiring and talent development track record
Experience with LLM platforms or proprietary data products
Prior startup exit or scale-up experience
In-office leadership presence matters
High ownership, low bureaucracy
Clear priorities and fast execution
Open technical debate with strong accountability
Shape the core technology behind next-generation investment intelligence
Build a top-tier engineering organization from the inside
Direct influence on company trajectory and product success
Work at the frontier of AI, data, and finance
Base salary: $250,000 to $300,000
Meaningful equity package
In-office in New York
No agency candidates
Apply if you want to build and lead a serious engineering organization solving hard problems.
Do not apply if you prefer slow cycles, heavy process, or purely managerial roles.
Skills Required
- 10 plus years in engineering leadership roles
- Significant experience in fintech or investment platforms
- Built and scaled data-heavy, AI-powered systems in production
- Led teams through rapid growth stages
- Strong technical background in modern backend architectures
- Comfortable diving into code and architecture when needed
- Proven hiring and talent development track record
- Experience with LLM platforms or proprietary data products
- Prior startup exit or scale-up experience
What We Do
We empower organizations and institutions with the capabilities to more effectively identify mental health challenges to ensure patients, team members, and constituents receive the care they need. Toggle offers a new form of artificial intelligence that merges advances in computational cognition with machine learning. We call it Comp Cog AI, and it predicts anxiety, depression, and suicidal planning using a single 3-minute assessment involving images. Its accuracy is cutting-edge against peer-reviewed findings for these three mental health challenges and is immune to manipulation or gaming, ensuring highly repeatable results. Fast, accurate & inexpensive, Toggle’s solution is built on the latest developments in neuroscience and supported by deep academic review and competitive government funding. Example Use Cases: - Rapid & regular screening for Military, Defence and Public Safety personnel - Screen for mental health during every visit to the Emergency Room or Medical Clinic - Triage and best route callers in crisis line and telehealth environments - Regularly assess at-risk groups remotely, triggering outreach where needed - Offer screening to students and the workforce to deliver timely intervention
