Job Description
Job Description
Senior AI Data Systems Engineer
Compensation : $180,000 - $260,000 USD
Location : San Francisco Bay Area (Hybrid, 2 days in-office)
Who Are We?
We are building the foundational infrastructure that powers the next generation of AI models for leading research labs and enterprises.
What's in it for you?
- High-Impact Work Build AI infrastructure used by top research labs and enterprises to train leading AI models.
- Technical Excellence Work at the forefront of distributed systems, large-scale databases, and AI-driven data pipelines.
- Fast-Paced Innovation Thrive in an environment that rewards ownership, rapid execution, and direct impact.
- Career Growth Your contributions directly impact product success and career advancement.
- Clear Ownership Drive end-to-end engineering solutions with autonomy and accountability.
What will you do?
As a S enior AI Data Systems Engineer , you will lead the design and development of high-performance, scalable data infrastructure that supports AI training workflows. Your expertise will power seamless data ingestion, storage, and streaming, enabling customers to manage massive datasets for training next-generation AI models. You will own key data infrastructure components, collaborating with cross-functional teams to deliver efficient, scalable solutions.
Develop Scalable Data Systems Design and optimize high-throughput data infrastructure, leveraging distributed databases, cloud-native solutions, and advanced data processing frameworks.Enhance AI Workflow Performance Improve indexing, querying, and storage efficiency to accelerate AI model training and deployment.Optimize Data Pipelines Build and maintain large-scale data pipelines using distributed queues, message brokers, and job management frameworks.Drive Engineering Excellence Mentor engineers, advocate for best practices, and contribute to technical knowledge-sharing.Improve System Reliability Work closely with support teams to troubleshoot and resolve performance bottlenecks.Advance AI Capabilities Enable real-time AI data workflows and enhance our platforms ability to handle large-scale, high-performance AI training workloads.What will you need?
5 years of experience in backend and data infrastructure engineering.Strong expertise in database architecture , including relational (PostgreSQL, MySQL), NoSQL (MongoDB, Cassandra), and cloud-native solutions (Google Spanner, AWS DynamoDB).Experience with distributed data systems , including message brokers (Kafka, RabbitMQ), job orchestration frameworks, and scalable storage architectures.Proficiency in backend programming using Python, Java, or TypeScript ; familiarity with Node.js and NestJS is a plus.Experience designing large-scale data pipelines for high-throughput data processing.Deep understanding of system performance optimization , indexing strategies, and data retrieval for AI applications.Cloud expertise with GCP (preferred), AWS, or Azure.Strong problem-solving skills , with a structured approach to tackling complex engineering challenges.Proactive mindset , with the ability to work independently and take ownership of mission-critical systems.Experience with AI-powered development tools , including GitHub Copilot and Cursor .Nice to Have
Experience with data warehousing (Snowflake, BigQuery).Familiarity with Kubernetes and DevOps tools (ArgoCD, DataDog).Background in AI training workflows , LLM-backed AI services, or AI data processing pipelines.Knowledge of memory optimization and performance tuning in data-intensive systems.Join us and help shape the infrastructure that powers the future of AI.
Salary : $180,000 - $260,000
