About the role

Role Overview

Sr. Data Engineer to evolve a modern data stack and help build the foundation for an emerging AI/ML platform. The role bridges data engineering, platform architecture, and machine learning enablement to deliver scalable, reliable, and ethical AI in production.

Responsibilities

Design, build, and maintain scalable systems for data ingestion, transformation, and storage with emphasis on testing and observability.
Implement frameworks, tooling, and automation to safely increase development velocity.
Build end-to-end AI/ML workflows, including:
- source ingestion and preparation
- training and tuning
- experimentation and productionization
- downstream integration (e.g., EHR modules, microservices, dashboards)
Support iterative model development and production operations/observability (accuracy, drift, bias, fairness, reproducibility).
Contribute to continuous improvement, knowledge-sharing, and mentoring peers.
Use AI tools as part of daily work to improve efficiency, quality, and decision-making.
Build production-grade services, including APIs that expose internal data/services to LLMs (noted via MCP servers).

Required Skills

Proficiency in SQL and Python; strong familiarity with modern data engineering frameworks, infrastructure, and tooling.
DataOps best practices: monitoring, pipeline automation, and CI/CD.
Knowledge of modern compute/ML frameworks/libraries: Spark, TensorFlow, PyTorch, scikit-learn.
Ability to build production APIs and services (including MCP servers for LLM access).
Collaborative, dependable mindset; strong drive to reflect and improve; humility to learn.
Comfort using AI tools in day-to-day workflows and continuously improving processes.

Nice-to-Haves

Prior experience with AI tools.
Curiosity and openness to experimenting with new tools and approaches.
Healthcare / behavioral health / EHR systems / regulated industry experience.

Education & Experience

Bachelor’s degree (or equivalent) in Computer Science, Data Science, Statistics, Engineering, or related.
5+ years experience in data engineering, platform engineering, or ML engineering.

Tools/Platforms Mentioned

Major cloud data platforms and tools: AWS/GCP, dbt, Airflow, Airbyte, Redshift/BigQuery.

About Octave

Octave is a modern behavioral health practice building a new standard for care delivery that is high-quality and accessible. The company operates in-person and virtual clinics across multiple states and partners with payers to make care more affordable through insurance. It also works to improve provider support and care effectiveness with evidence-based therapy.

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