Principal AI/ML Engineering Lead

This is a fully remote position, open to applicants in United States.

📋 Description

• Contribute to the overall platform development, including data ingestion, transformation, a canonical data model, entity resolution, an event backbone, configuration as code, and API and serving layers.

• Enhance DevOps and reliability through CI/CD practices, infrastructure as code, environment management, and observability involving metrics, logs, traces, and service level objectives.

• Collaborate with Security and IT teams on data classification and enforcement of access controls, management of secrets and keys, and implementing controls in compliance with HIPAA and HITRUST.

• Establish the foundation for the AI/ML platform, which encompasses model serving and an inference gateway, feature and training data pipelines, model lifecycle management, and integration of LLM with grounding and guardrails.

• Ensure that protected health information remains within controlled boundaries and utilize in-VPC or local inference as necessary to prevent data leakage.

• Work alongside current team leads to enhance AI and ML proficiency across platform, security, and DevOps teams while creating reusable patterns.

• Undertake additional responsibilities as required.

⛳️ Requirements

• A minimum of a Bachelor's Degree.

• 7-10+ years of experience in constructing and scaling production-quality machine learning or AI systems.

• Proven experience as a generalist Software Engineer with a focus on backend, infrastructure, and data.

• Significant hands-on experience in building and deploying AI/ML systems in production, including MLOps, model serving and inference infrastructure, feature and data pipelines, as well as integrating models into real-world applications.

• Strong experience with cloud technologies, preferably on Google Cloud (Vertex AI, BigQuery, Cloud Run, Pub/Sub, Cloud SQL, GKE); AWS or Azure equivalents are also acceptable.

• Proficiency in DevOps and reliability practices: CI/CD, Terraform or similar tools, containers, and Kubernetes, along with production observability.

• Solid expertise in data engineering, including SQL, pipeline tools such as dbt, and data warehousing.

• A security-oriented mindset with experience working in regulated environments handling sensitive data; familiarity with HIPAA or HITRUST is advantageous.

• Experience with LLM applications, encompassing retrieval, evaluation, guardrails, and knowledge graphs.

• Ability to navigate ambiguity and a strong inclination towards delivering results. You can specialize in one area while also adapting across the technology stack.

• Experience with entity resolution or master data management.

• Background in healthcare or another domain involving regulated data.

• Familiarity with GraphQL or a federated serving layer.

• Knowledge of privacy-enhancing technologies.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Opportunities for professional development and continuous learning.

• Flexible work hours and remote work options.

• A supportive and inclusive company culture.