Senior Software Engineer

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.