Innovation Lab Technical Lead

Peraton•,

2d•$80,000 - $128,000

About The Position

The Innovation Lab Technical Lead is a senior, cross-functional engineering leader responsible for the end-to-end development of the use cases in the lab. The Innovation Lab Technical Lead will unify the disciplines of cloud infrastructure, data/AI tooling, and CMS FPS (Centers for Medicare & Medicaid Services Fraud Prevention System) operational governance into a single point of technical authority for the development team. The Technical Lead oversees the design and deployment implementation architectures for a prioritized use case. Drives the operationalization of AI and data tooling ecosystems, and serves as the critical bridge between the Innovation Lab's AWS environment and the existing CMS FPS analytics and modeling processes, workflows, and governance structures. Requires a rare combination of deep hands-on engineering expertise, data platform fluency, and agility to support cross-functional teams.

Requirements

Bachelor's degree with 2+ years of relevant experience, Master's degree with 0+ years of experience, or High School diploma with 6+ years of experience in data science or a related technical field.
Demonstrated experience manipulating dataframes and performing analytical queries using SQL; proficiency programming in Python and/or R for data science and ML workflows
Hands-on experience with MLflow for integrated model governance, experiment tracking, model versioning, and automated release pipelines within the model development lifecycle.
Experience designing and implementing model development lifecycle optimizations, including automated model quality checks, testing frameworks, and governance validation processes.
Working experience with Snowflake and Databricks for large-scale data processing, ML pipeline development, and analytics workloads in a cloud-based environment.
Working knowledge of large language model (LLM) deployment, fine-tuning, and evaluation; experience integrating Generative AI use cases into production analytics platforms.
Familiarity with SDLC fundamentals and experience using GitHub for version control, branching, and collaborative code management.
Commitment to ensuring data security, quality, and governance are embedded in all implemented changes; familiarity with PII/PHI handling requirements and access-controlled data storage standards.
Excellent written and verbal communication skills; strong team player with the ability to support internal development teams and communicate platform changes to external stakeholders.
Ability to obtain and maintain a Public Trust clearance
US citizenship or Green Card holder required and must have been in the US for at least 3 of the last 5 years.

Nice To Haves

Experience with components of the Databricks E2 Platform, including Unity Catalog and Feature Store, for governed data and feature management.
API development experience or experience utilizing Databricks REST APIs for platform integration and workflow automation.
Advanced Apache Spark architecture knowledge and experience optimizing large-scale distributed data processing workloads.
Development with scripting languages such as Python or Bash to support automated CI/CD processes and pipeline orchestration.
Experience integrating large-scale analytics components to support model development across distributed data environments.
Prior experience working within CMS, including familiarity with CMS data systems, workflows, and governance structures.
Knowledge of healthcare claims data, Medicare/Medicaid program data, or federal health analytics use cases.
Experience applying AI/ML or advanced analytics to fraud, waste, and abuse (FWA) detection or program integrity use cases.
Experience with Confluence/JIRA for SAFe Agile project tracking and cross-functional documentation.

Responsibilities

Unify the disciplines of cloud infrastructure, data/AI tooling, and CMS FPS operational governance into a single point of technical authority for the development team.
Oversee the design and deployment implementation architectures for a prioritized use case.
Drive the operationalization of AI and data tooling ecosystems.
Serve as the critical bridge between the Innovation Lab's AWS environment and the existing CMS FPS analytics and modeling processes, workflows, and governance structures.