Senior AI Engineer (telecom domain) - UST / TMobile at Bellevue WA

[Aphrosoft Technologies]

Please send resume to anir...@aphrosoft.com 

Need somebody from the telecom domain and 10+ years of experience. 

Role : Senior AI Engineer – Privacy

Location : Bellevue WA

Client: UST / TMobile

The Senior AI Engineer – Privacy will design, build, and operationalize AI and agentic systems that power Client data privacy platform at scale. Embedded within the Data & Intelligence organization's Privacy practice, this engineer will apply large language models (LLMs), retrieval-augmented generation (RAG), multi-agent orchestration, and foundation model capabilities to automate, enhance, and scale privacy operations — including Data Subject Request (DSR) processing, consent management, regulatory compliance monitoring, and privacy impact assessment workflows — across a customer base of over 100 million.

You will collaborate with data engineers, full stack engineers, privacy product managers, and legal and compliance teams to deliver production-grade AI solutions. You will apply responsible AI principles, implement human-in-the-loop controls, and ensure audit logging and observability across AI-assisted privacy workflows. Your work will directly shape how T-Mobile meets its obligations under CCPA, CPRA, TCPA, and other state and federal privacy regulations.

AI Agent & LLM Engineering

• Design and build multi-agent systems, orchestration layers, and agentic workflows using frameworks such as LangChain, LangGraph, Google ADK, or equivalent.

• Develop and operationalize RAG (Retrieval-Augmented Generation) pipelines integrating LLMs (e.g. Claude, Gemini, GPT-4) into production privacy applications.

• Implement structured prompting, decision workflows, and tool orchestration — including MCP (Model Context Protocol)-based architectures — for autonomous agent systems.

• Build AI-powered automation for privacy operations including intelligent DSR routing, threshold monitoring, agentic data quality checks, and automated regulatory notifications.

• Enable human-in-the-loop controls and escalation paths for AI-assisted decisions in sensitive privacy workflows.

Data & ML Engineering

• Build and optimize data pipelines using Azure Data Factory, Databricks, Snowflake, or PySpark to support AI model training, fine-tuning, and inference.

• Apply prompt engineering, few-shot learning, and fine-tuning techniques to adapt foundation models for privacy-specific use cases.

• Implement vector databases and embedding strategies to power RAG pipelines over Client internal privacy knowledge bases and policy documents.

• Ensure data quality, lineage, and governance standards are maintained across all AI training and inference pipelines.

Cloud & MLOps

• Deploy and manage AI workloads on Azure or AWS, including serverless inference endpoints, container registries, and GPU/compute resources.

• Build and maintain CI/CD pipelines for AI model deployment using GitLab or Azure DevOps, applying MLOps best practices.

• Implement monitoring, alerting, and performance tracking for production AI models and agent systems using Splunk, AppDynamics, or Grafana.

• Apply containerization (Docker) and orchestration (Kubernetes) to ensure scalable and reliable AI service deployments.

Thanks and Regards,

Anirban Panja

Aphrosoft Technologies

anir...@aphrosoft.com

[Jadi Rajesh]

Hi,

Hope you are doing well,

Please find the attachment of my consultant profile for your below requirement & I feel that my consultant skills and experience are a great fit for this position.



Thanks & Regards

Jadi Rajesh
Bench sales Recruiter
Email- raj...@nisktech.com
Direct - 2542373911
440 BENMAR DRIVE, SUITE 2291,
HOUSTON, TX 77060
LinkedIn- www.linkedin.com/in/rajesh-jadi-563882411

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