Principal Engineer - AI Data and Infrastructure, Remote

Architect complex systems and make critical technical decisions.

Solve challenging technical problems with innovative solutions.

Mentor engineers and promote engineering excellence across teams.

Align technical strategies with business goals through cross-functional collaboration.

Contribute to technical roadmaps and strategic planning.

Evaluate new technologies and lead innovation initiatives.

BS/BTech (or higher) in Computer Science, Engineering or a related field required

10+ years of production-level experience as an engineer building highly scalable systems

6+ 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)

10+ years of production-level experience as an engineer building highly scalable and reliable infrastructure

Strong background in architecting or implementing AI-driven features - with the ability to translate AI capabilities into scalable and performant products

Proven track record in end-to-end architecture and delivery - guiding large teams (50+ engineers) across multiple product areas from initial conception through maturity.

Ability to lead and mentor senior engineering talent, shaping architecture decisions and technical direction across multiple teams

Demonstrated success evaluating and adopting emerging technologies to drive company-wide technical strategies

Experience working with data ingestion systems and optimizing performance for handling large-scale data processing and analysis

Deep hands-on expertise with cloud infrastructure (AWS preferred), event streaming (Kafka), data processing (Databricks and Kafka), and large-scale database systems

Familiarity with database replication, sharding and other techniques for scalability and high availability of databases

Experience engineering systems for scalability, high availability, and security — with a focus on sensitive or regulated data

Experience building observability platforms, performance monitoring, and optimization frameworks for large-scale systems and infrastructure.

Expertise in containerization/orchestration technologies (Docker, Kubernetes) and modern CI/CD pipelines

Experience with health-tech systems (like Electronic Health Records, Clinical data, etc.) is desired