Sr. AI/ML Engineer

We re seeking a Senior AI/ML Engineer to support a large-scale cloud-based analytics platform. This mission-critical Platform-as-a-Service (PaaS) enables secure, scalable development and deployment of traditional and generative AI models. The platform integrates tools like Databricks, JupyterHub, SageMaker, Bedrock, and more. In this role, you ll help build reusable solutions, improve infrastructure readiness, and ensure platform services meet technical, compliance, and performance standards.

Responsibilities:

• Build and maintain robust pipelines for data ingestion, exploration, feature engineering, and model training across Databricks and AWS-native services.
• Operationalize tools such as MLFlow for experiment tracking, model registry, versioning, and lifecycle governance.
• Integrate with T-Cloud Bitbucket and CI/CD pipelines (e.g., Bamboo) to enable secure, traceable development workflows.
• Configure and manage IRS-compliant AWS S3 feature stores, ensuring UNAX-compliant isolation and secure access per team.
• Develop and orchestrate AWS services (Lambda, RDS, SNS, EventBridge) to support automated model promotion and metadata tracking.
• Support GenAI enablement by engineering reusable, secure pathways for customers to leverage AWS Bedrock and SageMaker for LLM-based applications.
• Collaborate across the Infrastructure, Customer Success (CSx), and ATO/OneSDLC teams to support onboarding and productionalization for IRS customer use cases.
• Implement and maintain Responsible AI tooling, including the Responsible AI Toolbox, to support auditability and ethical deployment practices.
• Produce high-quality documentation and reusable code artifacts that simplify customer experience and platform adoption.
• Support platform-wide upgrades (e.g., Databricks E2), refactoring of inherited IaC, and improvements in CI/CD automation and monitoring.

Requirements:

• Bachelors degree and seven (7) years or more of related experience or Masters and five (5) or more years of related experience.
• Strong experience in AI/ML engineering, with significant hands-on experience using Databricks, JupyterHub, and AWS AI/ML services (e.g., SageMaker, Bedrock, Lambda, RDS, S3).
• Proficient in Python, SQL, Spark, and machine learning frameworks used in both model development and deployment.
• Demonstrated experience with MLFlow, CI/CD pipelines, infrastructure-as-code, and Git-based version control.
• Deep familiarity with building secure, compliant ML infrastructure in a regulated federal environment.

Desired:

• Prior experience supporting AI/ML in regulated environments such as IRS, Treasury, or other federal agencies.
• Familiarity with Immuta, Trustworthy AI controls, and model auditability frameworks.
• AWS certification or similar credentials in cloud engineering or DevOps.
• Exposure to customer onboarding, cross-team collaboration, and platform-as-a-service delivery models.
• Security Clearance desired