3 days ago
Base Salary
$224k - $264k/yr
Responsibilities
- Architect and build auditable AI agent systems, including multi-agent workflows, orchestration layers, and production infrastructure.
- Evaluate emerging AI models, tools, and development patterns and guide their adoption into robust production systems.
- Design explainable modeling and reasoning systems for financial-services use cases.
- Build Python/React internal applications and platforms for authoring, validating, and deploying AI-powered analysis.
- Own distributed backend infrastructure including event-driven workers, job pipelines, and multi-stage processing systems.
- Establish automated AI evaluation, hallucination detection, quality assurance, monitoring, and compliance guardrails.
- Drive cross-team technical decisions involving schemas, API contracts, system boundaries, and service architecture.
- Contribute to full-stack application development and lead engineering initiatives across teams and partners.
- Promote engineering and architecture best practices, adopt new AI techniques, and mentor senior engineers.
Requirements
- 8+ years of engineering experience leading complex systems from design through production.
- Hands-on experience designing, building, and shipping production software systems using AI development tools, especially AI-powered software.
- Strong software engineering and application-architecture skills with a record of establishing best practices.
- Expertise in Python, including asynchronous services, type-safe code, and scalable systems.
- Strong distributed-systems fundamentals, including event-driven architectures, message queues, job state machines, and worker patterns.
- Relational database fluency and strong data-modeling ability.
- Full-stack capability, including building product-quality React/TypeScript user interfaces.
- Experience leading technical teams or acting as a force multiplier across engineering.
- Preferred: production AI/ML systems, agent architectures, LLM integration, model evaluation, AI pipelines, multi-agent systems, or AI orchestration layers.
- Preferred: data engineering and large-scale data pipelines, cloud infrastructure and infrastructure as code, quantitative finance or wealth-management technology, or regulated-industry experience involving compliance, auditability, or explainability.
Benefits
- Competitive cash compensation and meaningful equity.
- 100% employer-paid medical, dental, and vision coverage, plus disability coverage.
- Flexible paid time off and paid parental leave.
- Catered meals.
- Based in New York City with work in the office four days per week.