Senior AI Engineer - Privacy

We are looking for Senior AI Engineer - Privacy for our client in Bellevue, WA.

Job Title: Senior AI Engineer - Privacy

Job Location: Bellevue, WA

Job Type: Contract

Job Overview:

Pay Range: $70/hr - $75/hr

• The Senior AI Engineer Privacy will design, build, and operationalize AI and agentic systems that power the data privacy platform at scale.
• This role involves applying large language models, retrieval-augmented generation, multi-agent orchestration, and foundation model capabilities to automate and enhance privacy operations.

Requirement/Must Have:

• 7 years of experience as an AI Engineer with a focus on privacy.
• 7 years of experience with Azure Data Factory and Azure.
• 5 years of experience with Databricks and Snowflake.

Responsibilities:

• Design and build multi-agent systems, orchestration layers, and agentic workflows using frameworks such as LangChain or equivalent.
• Develop and operationalize retrieval-augmented generation pipelines integrating large language models into production privacy applications.
• Implement structured prompting, decision workflows, and tool orchestration for autonomous agent systems.
• Build AI-powered automation for privacy operations including intelligent data subject request routing and automated regulatory notifications.
• Enable human-in-the-loop controls and escalation paths for AI-assisted decisions in sensitive privacy workflows.
• Build and optimize data pipelines using Azure Data Factory, Databricks, Snowflake, or PySpark to support AI model training and inference.
• Apply prompt engineering and fine-tuning techniques to adapt foundation models for privacy-specific use cases.
• Implement vector databases and embedding strategies to power retrieval-augmented generation pipelines over internal privacy knowledge bases.
• Ensure data quality, lineage, and governance standards are maintained across all AI training and inference pipelines.
• Deploy and manage AI workloads on Azure or AWS, including serverless inference endpoints and GPU resources.
• Build and maintain CI/CD pipelines for AI model deployment using GitLab or Azure DevOps.
• Implement monitoring, alerting, and performance tracking for production AI models and agent systems.
• Apply containerization and orchestration to ensure scalable and reliable AI service deployments.
• Implement responsible AI principles across all AI systems used in privacy operations.
• Ensure AI-assisted workflows comply with applicable state and federal privacy regulations.
• Design and maintain audit trails and human-in-the-loop checkpoints for AI decisions affecting consumer privacy rights.
• Collaborate with legal, compliance, and privacy operations teams to translate regulatory requirements into AI solution guardrails.
• Partner with data engineers, full stack engineers, product managers, and privacy stakeholders to deliver end-to-end AI-powered privacy solutions.
• Mentor junior engineers on AI/ML engineering practices and responsible AI design principles.
• Produce clear technical documentation and architecture diagrams for AI systems in production.
• Contribute to internal accelerators and reusable AI component libraries.