Aledade, Inc. is seeking a Staff Software Engineer - Data AI Agent to focus on building and maintaining a tool designed to automate data analysis use cases. The role involves partnering with stakeholders, proposing design patterns, and mentoring engineers while driving the development of scalable solutions 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