Staff Software Engineer - Data AI Agent

Aledade is focused on building and maintaining a Data AI agent designed to automate data analysis use cases. In this role, you will partner with stakeholders, propose design patterns, and deliver scalable solutions while mentoring engineers and maintaining high-quality engineering standards.

Responsibilities:

• Identify and develop scalable and performant solutions
• Work across discipline to shape product strategy and execution
• Develop the foundations of code architecture and quality
• Mentor and coach engineers
• Set and uphold the standard for engineering processes to support high-quality engineering

Requirements:

• BS/BTech (or higher) in Computer Science, Engineering or a related field required
• 8+ years of production-level experience as an engineer building highly scalable systems
• 4+ years of experience acting as a trusted technical decision-maker in a team setting, solving for short-term and long-term business value
• 4+ years of experience working with SQL or other database querying languages on large multi-table data sets
• Experience architecting, developing, and deploying large-scale distributed systems at scale
• Experience with cloud technologies, e.g., AWS, Azure, GCP
• Experience building continuous integration and continuous development (CI/CD) pipelines
• Strong familiarity with server-side web technologies (eg: Java, Python, Scala, C#, C++, Go)
• 8+ years of production-level experience as an engineer building highly scalable and reliable infrastructure
• Experience in designing, building and optimizing data pipelines and ETL processes
• Proficiency in working with both OLTP and OLAP database technologies (Postgres, Snowflake, Databricks)
• Experience with data modeling (bonus points for dbt experience)
• Experience building AI agents is a big plus (MCP tools, evals, feedback loop)
• Experience building and maintaining APIs (REST, GraphQL)
• Ability to drive projects and bring the team along - shaping work for other engineers is key
• Familiarity with replication and pub-sub technologies (Kafka)
• Experience in performance monitoring and optimization of infrastructure (calibrating Kubernetes resources)
• Experience with containerization and orchestration technologies such as Docker and Kubernetes
• Experience building continuous integration and continuous deployment (CI/CD) pipelines
• Experience with security and systems that handle sensitive data