Description
We are looking for a visionary Staff Engineer to serve as the technical North Star for our data and AI-driven platforms. In this role, you will be responsible for the evolution of our core architecture, moving us toward a future where real-time data processing and AI are seamlessly integrated into every facet of our product.
As our data ecosystem grows in complexity, we need a leader who can navigate the intersection of high-performance backend engineering and modern AI capabilities. You will tackle "unsolved" problems,designing systems that handle petabytes of data with millisecond latency, architecting multi-tenant API ecosystems, and building the infrastructure that delights our customers who are leveraging our AI solutions for their everyday work.
**Key Responsibilities:"
- Architectural Leadership: Design and oversee the implementation of highly scalable, distributed backend systems and microservices using Java, Kotlin, and Python.
- Data Strategy: Define the data architecture and modeling standards for both relational (SQL) and non-relational systems, ensuring data integrity, security, and high availability.
- Streaming & Batch Processing: Lead the design of real-time data pipelines (e.g., using Dataflow, Pub/Sub, or Kafka) and batch processing frameworks to handle petabyte-scale data efficiently.
- AI Integration: Drive the "AI-first" engineering culture by integrating LLMs, machine learning models, and RAG (Retrieval-Augmented Generation) patterns into production workflows using GCP Vertex AI.
- Cloud Excellence: Optimize GCP infrastructure for performance and cost, leveraging GKE, BigQuery, and Cloud Spanner to support global-scale operations.
- API & Ecosystem Design: Set the standard for API development (REST, GraphQL, gRPC), ensuring seamless integration across internal services and external partners.
- Technical Governance: Conduct architecture reviews, define CI/CD best practices, and ensure the team maintains a high bar for code quality, testing, and observability.
- Mentorship: Act as a force multiplier by mentoring Senior Engineers, fostering a culture of continuous learning and technical excellence.
**Requirements:"
- Bachelor’s Degree in Computer Science, Data Science, or a related field
- 10+ years of professional software engineering experience, with at least 5 years using Python and SQL
- 5 years experience building and consuming APIs to drive complex data integrations across distributed systems.
- 5 years experience migrating or building large-scale architectures on GCP.
- 4+ years in a Senior or Staff capacity, overseeing large-scale distributed systems.
- 2+ years Practical experience using LLM APIs or building GenAI-enabled applications
- Experience in a "Product-led" engineering environment where you have directly influenced product features through technical capability.
**Preferred Qualifications:"
- Contributions to Open Source projects or a recognized presence in the tech community (talks, blogs, etc.)
- Experience with MLOps frameworks (Kubeflow, MLflow)
- Advanced degree (MS or PhD) in Computer Science, Data Science, or a related field