Lead Product Management & Develop

This position requires office presence of a minimum of 5 days per week and is only located in the location(s) posted.  No relocation is offered.

Join AT&T and reimagine the communications and technologies that connect the world. Our Consumer Technology experience team is delivering innovative and reliable technology solutions to power differentiated, simplified customer experiences. Bring your bold ideas and fearless risk-taking to redefine connectivity and transform how the world shares stories and experiences that matter. When you step into a career with AT&T, you won’t just imagine the future-you’ll create it.
 

We are seeking a Lead Product Owner with a strong foundation in data engineering and hands‑on experience across AI/ML, Computer Vision, and Large Language Model (LLM) platforms to lead the strategy, roadmap, and delivery of scalable data and intelligence platforms across cloud (AWS), edge, and hybrid environments.

This role bridges business strategy and advanced AI execution, translating complex use cases into production‑grade analytics, ML, and GenAI solutions.

Key Responsibilities:

• Own the end‑to‑end product lifecycle for Data, AI/ML, Computer Vision, and LLM platforms

• Define platform roadmaps aligned with business outcomes and customer value

• Translate AI/ML and GenAI capabilities into clear, actionable product requirements

• Partner with engineering, data science, and architecture teams to deliver scalable, secure platforms

• Drive prioritization, Agile execution, and outcome‑based delivery

• Evaluate build vs. buy decisions across data, ML, CV, and GenAI stacks

Required Competencies:

Data Engineering & Platforms

• Experience with data ingestion, preprocessing, transformation, and governance pipelines

• Hands‑on familiarity with PostgreSQL and structured data modeling

• Experience supporting batch and streaming analytics workloads

Machine Learning – Hands‑On

• Experience with supervised and unsupervised learning techniques

• Working knowledge of Regression, Clustering, KNN, Decision Trees, Random Forest

• Familiarity with Bagging, Boosting, and XGBoost

• Understanding of Gini Index, Entropy, and Information Gain

• Experience with model performance evaluation and improvement

• Experience with Computer Vision ML, including image/video‑based feature extraction, object detection or classification, and integrating CV models into analytics or AI workflows

Exploratory Data Analysis

• Hands‑on experience with EDA, data preprocessing, and feature engineering

• Experience conducting Univariate and Bivariate Analysis

• Ability to translate analytical outputs into business recommendations

LLM & GenAI Platforms

• Hands‑on experience with Large Language Models (LLMs) and GenAI workflows

• Experience using Amazon Bedrock for model access, embeddings, and orchestration

• Familiarity with Anthropic models (Claude / Sonnet or similar)

• Experience implementing Retrieval‑Augmented Generation (RAG) patterns

• Understanding of prompt engineering, grounding, and context management

Vector & Search Systems

• Hands‑on experience with OpenSearch for hybrid and vector search

• Familiarity with embedding generation, storage, and similarity search

Programming & Analytics Tools

• Hands‑on experience with Python

• Proficiency with NumPy, Pandas, and Seaborn

• Experience reviewing notebooks, POCs, and analytics pipelines

Cloud, Edge & Hybrid

• Experience working with AWS cloud‑native services

• Familiarity with edge inference and hybrid cloud‑edge architectures

• Understanding of latency, cost, and deployment trade‑offs

Required Qualifications

• 5+ years of experience in Product Management or Product Ownership

• Strong background in data platforms, analytics, AI/ML, and GenAI systems

• Proven ability to work across business, engineering, and data science teams

• Strong communication skills with technical and executive stakeholders

Preferred Qualifications

• Experience with MLOps / LLMOps practices

• Exposure to conversational AI, RAG systems, or agent‑based architectures

• Experience in IoT, edge AI, real‑time analytics, or computer vision domains