Senior Software Engineer, Data Processing

Ingestion & Processing Systems

• Design, build, and operate the ingestion systems that process large volumes of multimodal data into usable, well-structured datasets
• Own the ingestion path end to end, from how data lands to how it is validated, processed, tracked, and made available downstream
• Build modality-specific processing steps for real-world source data, such as medical imaging processing, audio and video metadata extraction, quality validation, and notes processing
• Build parsers, validators, and normalization logic that can systematically handle messy, non-standard, and high-variance source formats
• Turn repeated one-off data handling work into reusable processing patterns, internal tooling, and platform capabilities

Scale, Performance & Reliability

• Build for high volume and high throughput, optimizing systems for reliability, cost, and speed
• Work across distributed and parallel compute systems to process workloads that do not fit well on a single machine
• Choose the right execution model for the workload, including batch processing, distributed execution, and modern compute patterns for unstructured data and inference-heavy processing
• Diagnose and resolve bottlenecks across ingestion and processing systems, and keep performance from degrading as volume and modality complexity grow

Data Quality, Security & Compliance

• Build validation and quality checks that catch bad, incomplete, or malformed data before it propagates downstream
• Handle sensitive and regulated data, including PHI, with the security and care the domain demands, including de-identification where required
• Track provenance, metadata, and usage constraints through the ingestion path so downstream use remains compliant and auditable
• Raise the quality bar for observability, debuggability, and operational reliability across the ingestion layer

Cross-Functional Partnership

• Partner with product and Data Lab to support new modalities, new partner requirements, and non-standard source data
• Work directly with partner engineering teams when needed to translate source-system realities into robust ingestion and processing design
• Surface recurring patterns that are worth standardizing into reusable transforms, validators, and internal tooling
• Help shape how Protege handles new data types as the platform expands into more complex data environments

What You Bring

Must Haves

• 5+ years building and operating production backend or data systems, with real experience in data processing at scale
• Hands-on experience designing and running large-scale data pipelines
• Strong programming skills in Python
• Experience with distributed data processing
• Strong proficiency with AWS
• Comfort with messy, varied, high-volume data and high ambiguity, with a knack for finding patterns in complex environments
• Attention to detail without losing speed, and a bias to action
• Excited to work on a product built around moving and processing large volumes of data
• Curious, tenacious, and proactive

Nice to Haves

• Experience processing one or more specific modalities at scale: medical imaging (e.g., DICOM), text, audio or video
• Background working with sensitive or regulated data environments (HIPAA, healthcare compliance, PHI handling)
• Experience with streaming systems or workflow orchestration (e.g., Airflow, Dagster)
• Experience with GCP and Azure
• Prior startup experience as a founding or early engineer
• Familiarity with ML, NLP, or LLM-based systems, including embeddings and fine-tuning