Job Title: Staff Software Engineer, Agentic Patient Outreach

Company Name: Aledade, Inc.

Job Url: https://jobright.ai/jobs/info/69bb24393b74eb1e2c899190

Job Description: 
Aledade, Inc.
· 3 hours ago
Staff Software Engineer, Agentic Patient Outreach

United States

Full-time

Remote

Lead/Staff

8+ years exp
83%
GOOD MATCH
89%
Exp. Level
73%
Skill
39%
Industry Exp.
Aledade, Inc. is seeking a Staff Software Engineer to drive the design, delivery, and evolution of critical systems for patient outreach. This role involves hands-on engineering and architectural ownership, focusing on building scalable data-intensive systems that integrate with AI models for effective patient care delivery.
Healthcare
Wellness
Health Care
Medical
Primary and Urgent Care

Comp. & Benefits

H1B Sponsor Likely

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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

Qualification

Represents the skills you have
Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Scalable systems architecture
Distributed systems
SQL
Database querying
Cloud technologies
AWS
Azure
GCP
CI/CD pipelines
Server-side programming
Java
Python
Scala
C#
C++
Go
Event-driven architectures
Streaming platforms
Kafka
Containerization
Docker
Kubernetes
NoSQL databases
Data partitioning
Sharding
Indexing strategies
Data pipelines
Workflow orchestration
Apache Airflow
AWS Glue
Required
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)
Preferred
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