11 days ago
Remote, WorldwideStaff+
Responsibilities
- Own the architecture and evolution of extraction, load, and pipeline systems serving more than 500 integrations.
- Identify architectural bottlenecks and drive performance, reliability, and scalability improvements across distributed systems.
- Modernize legacy systems, including LES, DSAS, and ULS, into scalable AI-native infrastructure.
- Design and implement agentic development frameworks for codebase maintenance, continuous improvement, validation, testing, and rollout.
- Document technical decisions and set standards for code quality, reliability, and performance.
- Mentor engineers on AI-assisted development practices and help them ship faster while managing risk.
- Collaborate with product and AI teams on agentic framework rollout and new integration capabilities.
Requirements
- At least 7 years of hands-on backend engineering experience, including at least 2 years in a principal- or architect-level role owning production systems.
- Experience designing and scaling complex systems rather than only maintaining them.
- Hands-on experience with AI-assisted development, Claude Code, agentic coding, and building agentic frameworks for code maintenance and rollout.
- Strong distributed systems experience with Kubernetes, workflow orchestration such as Temporal, and message queues such as RabbitMQ.
- Experience building secure, resilient systems that are difficult to break or breach.
- Experience with observability, alerting, and incident response at scale.
- Solid SQL and query optimization experience across PostgreSQL and ClickHouse.
- Ability to define engineering standards and drive adoption across a team is preferred.
- Experience migrating legacy pipeline systems is preferred.
- Background in data integration or ETL infrastructure is preferred.
- Ability to work within the EST timezone and fluency in English.
Benefits
- Remote-first work environment.
- 20 PTO days and US holidays.
- Stock options.
- Professional development reimbursement.
- Optional relocation assistance to Latin America after the trial period.
- Direct influence over platform architecture and freedom to experiment with an AI-native technology stack.