[Hiring] Senior Principal Machine Learning Engineer @Transcarent

Role Description

The Sr. Principal ML Engineer is the most senior individual-contributor technical role in our Data and AI organization — spanning our data platform, data warehouse, ELT pipelines, ML systems, and GenAI capabilities. This person sets technical direction with full autonomy, moving fluidly between deep hands-on execution and high-level architecture to unblock our highest-leverage initiatives, and serves as a technical multiplier for the broader engineering team.

What you'll do:

• Own the technical architecture and roadmap across our data platform, warehouse, ELT pipelines, ML systems, and GenAI components.
• Independently identify, scope, and resolve systemic architectural issues across the Data and AI/ML stack.
• Contribute directly to the codebase with high velocity, moving fluidly between implementation and high-level design.
• Plan and deliver complex initiatives spanning multiple teams and systems, proactively surfacing risks and decisions to leadership.
• Embed data governance, quality, lineage, and observability practices into every initiative from the outset.
• Partner with cross-functional stakeholders to clarify requirements and own the technical path from framing through delivery.
• Raise the technical bar across the organization through code reviews, design feedback, and direct coaching.
• Design fault-tolerant distributed data pipelines with checkpointing, replay, and schema evolution.
• Establish end-to-end data lineage, data quality SLAs, and automated data contract enforcement across platform initiatives.

Qualifications

• 12+ years of professional software/data engineering experience, including significant time as a senior IC at Principal level or above.
• Expert-level command of data engineering fundamentals: distributed processing (Spark, Flink), stream/batch pipelines, and data warehouse/lakehouse architecture.
• Strong ML engineering proficiency across the model lifecycle, from training and evaluation through deployment and production monitoring.
• Hands-on experience with modern GenAI/LLM workflows, including RAG architectures, fine-tuning, and prompt engineering.
• Cloud-native platform fluency (AWS, GCP, or Azure) and proficiency in Python and SQL.
• Demonstrated ability to lead complex, cross-functional technical initiatives without relying on organizational authority.
• Excellent written and verbal communication skills with both technical and non-technical audiences.
• Experience tuning warehouse/lakehouse performance through partitioning, query optimization, and workload isolation.
• Experience implementing model drift detection, reproducible ML deployments, and production rollback strategies.
• Experience evaluating RAG quality using retrieval metrics, groundedness testing, and automated regression gates.

Requirements

• Experience with Databricks, dbt, Kafka, and MLflow or equivalent ecosystem tools.
• Experience in healthcare, benefits, or another regulated, compliance-sensitive industry.
• Track record of using GenAI tools as a velocity and quality multiplier.
• Experience defining data governance and observability frameworks at platform scale.
• Prior experience mentoring senior engineers or leading technical communities of practice.

Benefits

• Individual contributor role; the most senior IC in the Data and AI organization, with broad architectural scope and no direct reports.
• Provides technical mentorship and coaching as part of day-to-day delivery.
• Remote US work location expectations.
• Minimal travel expectations (occasional team or offsite travel).