Software Engineer
Series-A AI Start-Up
Palo Alto (on-site)
Up to $300k base + equity
Our client is an AI-focused company committed to reshaping enterprise-level access to unstructured data. Their advanced embedding and retrieval solutions are built for large-scale applications and designed to optimize intelligent data retrieval, enabling powerful low-latency performance across diverse industries. Join their team of experts from leading academic institutions and top tech firms to work on high-impact solutions that drive intelligent, enterprise-grade systems.
Job Description
As a Data Infrastructure and Storage Engineer, you’ll be at the forefront of designing and optimizing data processing and storage systems that support our AI-driven applications. You’ll build resilient infrastructure for handling massive datasets, ensuring efficient storage, retrieval, and processing to support data-intensive workflows in a high-throughput environment.
Key Responsibilities
- Data Infrastructure Design: Architect, build, and optimize data storage and processing systems to support scalable, low-latency data retrieval and embedding pipelines.
- Performance Optimization: Optimize data pipelines to handle large-scale data processing, ensuring high performance and minimal latency for real-time applications.
- Data Management and Security: Develop and maintain systems for secure, compliant, and resilient data storage, with a focus on backup, recovery, and data integrity.
- Tooling and Automation: Design and implement automation for data ingestion, ETL (Extract, Transform, Load) processes, and data pipeline orchestration.
- Collaboration: Partner with backend and cloud engineers to integrate storage solutions into our broader infrastructure, ensuring seamless data accessibility across teams.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
- Experience: 3+ years of experience in data engineering, data infrastructure, or related roles, with a focus on large-scale data storage and processing.
- Technical Skills:
- Proficiency in database technologies (SQL and NoSQL, such as PostgreSQL, Cassandra, MongoDB).
- Experience with cloud-based data storage solutions (AWS S3, Google Cloud Storage, etc.) and big data processing frameworks (Spark, Hadoop).
- Strong skills in data pipeline automation tools (Airflow, Prefect) and containerization technologies (Docker, Kubernetes).
- Knowledge of data security best practices and compliance standards.
- Attributes:
- Analytical mindset with a focus on scalability and efficiency.
- Proactive problem-solving skills to address challenges in data infrastructure.
- Strong communication and collaboration abilities, with a team-oriented approach.
Why Join Us?
- Innovative Technology: Engage with cutting-edge data processing and storage technologies.
- High Impact: Help shape data infrastructure that drives AI solutions for industry applications.
- Professional Growth: Thrive in a team-oriented environment that encourages learning and career advancement.
If data engineering and building large-scale, high-performance storage solutions excite you, we’d love to connect. Apply today to join a mission-driven team pushing the boundaries of AI and data infrastructure innovation.
