Staff Software Engineer, Agentic Patient Outreach - Aledade

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.

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).

Own the architecture and technical roadmap for complex, cross-cutting systems, ensuring they are secure, scalable, and maintainable.

Lead by example through high-quality design and code, particularly in distributed systems, APIs, and cloud-native services.

Partner closely with product, platform, and cross-functional stakeholders to translate business goals into robust technical solutions.

Raise the technical bar by providing mentorship, design reviews, and guidance to senior and mid-level engineers.

Drive engineering excellence, including observability, reliability, performance, and operational best practices (e.g., CI/CD, incident response, and postmortems).

Influence and evolve engineering standards, patterns, and best practices across the organization.

Bring deep expertise in distributed systems, event-driven architectures, and streaming platforms (e.g., Kafka) and know how to design for scalability, resiliency, and fault tolerance.

Demonstrate strong hands-on experience with containerization and orchestration technologies such as Docker and Kubernetes, including operating services in production.

Have in-depth knowledge of database systems, including both SQL and NoSQL databases, with practical experience in data partitioning, sharding, and indexing strategies for large-scale datasets.

Bring strong proficiency in at least one modern server-side language (e.g., Java, C#, Python), with a strong preference for Python.

Regularly participate in and improve code reviews, architectural discussions, and feature planning sessions, helping drive high-quality technical and product decisions.

Have hands-on experience with data pipelines and workflow orchestration tools (e.g., Apache Airflow, AWS Glue, or similar technologies).

Have experience with systems that handle sensitive data, including architecting solutions that incorporate best practices for security, authentication/authorization.

Have experience building or integrating systems that leverage ML/AI models for real-time inference, including attention to latency, reliability, observability and ongoing model evaluation.

Experience working with systems that integrate with LLMs and generative AI is highly desirable, but not required.