Sr. Software Development Engineer, RBKS AI Data Management
This role is responsible for leading the design and implementation of innovative, scalable data solutions to support our growing AI initiatives.
You will work across multiple SDE organizations, Applied Science teams, and partner groups to build flexible, resilient data pipelines that enable our researchers to access high-quality training data just-in-time.
As a Sr. SDE, you will excel at solving ambiguous, complex problems and proactively mitigating risks before they become roadblocks.
The key responsibilities include:
* Conducting a comprehensive analysis of existing annotation workflows and developing automation tools to streamline manual tasks.
* Designing and deploying scalable, fault-tolerant data collection, annotation, and delivery pipelines to support the growing needs of our Applied Science teams.
* Collaborating with SDE, Data Engineering, and Applied Science teams to define requirements and ensure seamless integration of data solutions.
* Automating data workflows and building reusable, self-service capabilities to increase the speed and agility of our data delivery.
* Proactively identifying and mitigating technical risks, demonstrating solid judgment in determining when to escalate.
* Fostering a culture of testing, monitoring, and continuous improvement across data systems.
The strategic responsibilities include:
* Developing the long-term technical strategy and roadmap for the Data Management ecosystem, aligning with the organization's vision of delivering data for AI models with minimal manual intervention.
* Assessing emerging technologies and data management trends, and evaluating their potential impact on our data architecture and delivery capabilities.
* Decomposing ambiguous, complex problems into simplified, scalable solutions that reduce friction and improve flexibility.
* Communicating technical designs, trade-offs, and outcomes effectively to senior leadership (Director level and above).
* Fostering consensus and alignment across teams to drive coherent, enterprise-wide approaches to data challenges.
* Actively mentoring and developing more junior SDEs within the organization.
BASIC QUALIFICATIONS
* Experience as a full-stack software engineer, with a track record of delivering highly scalable, mission-critical data systems.
* Proficiency in designing and building distributed, fault-tolerant data pipelines and batch/streaming data processing workflows.
* Strong programming skills in languages like Java, Python, Scala, or Golang, with a deep understanding of software engineering best practices.
* Hands-on experience with modern data storage and processing technologies, such as Kafka, Spark, Hadoop, Cassandra, Redshift, or BigQuery.
* Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP) and infrastructure-as-code tools (e.g., Terraform, CloudFormation).
* Expertise in developing and implementing robust monitoring, alerting, and automated remediation for data systems.
* Experience with agile software development methodologies and tools (e.g., Jira, GitHub, CI/CD pipelines).
* Strong analytical and problem-solving skills, with the ability to tackle ambiguous, complex challenges.
* Excellent verbal and written communication skills to effectively collaborate with cross-functional teams.
* Bachelor's degree in Computer Science, Software Engineering, or a related field.
PREFERRED QUALIFICATIONS
* Experience designing and building large-scale data platforms to support machine learning and artificial intelligence use cases.
* Track record of delivering complex, cross-functional data projects that drive measurable business impact.
* Familiarity with data engineering best practices around data quality, lineage, governance, and lifecycle management.
* Understanding of machine learning data workflows, including data collection, annotation, feature engineering, and model training/deployment.
* Knowledge of data privacy and security frameworks (e.g., GDPR, CCPA) and experience implementing solutions to address compliance requirements.
* Familiarity with low-code/no-code development tools and their application in data automation and self-service capabilities.
* Proven ability to mentor and lead more junior engineers, fostering their technical growth and career development.
* Experience in delivering presentations and technical roadmaps to executive-level stakeholders.
* Background in applied research or academic work involving large-scale data processing and analysis.
* Master's degree in Computer Science, Software Engineering, or a related field.