Technical Product Manager – AI & Data Products

AT&T

Technical Product Manager building AI-native internal products at AT&T. Collaborating with engineering to deliver scalable solutions and drive product execution.

Posted 6/12/2026full-timeDallas • Texas • 🇺🇸 United StatesSeniorLead💰 $158,200 - $237,400 per yearWebsite

Tech Stack

Tools & technologies

CloudSQL

About the role

Key responsibilities & impact

Translate strategy into buildable product
Translate product strategy and business priorities into scoped, buildable releases, including PRDs, user stories, acceptance criteria, and technical requirements that engineering teams can execute without guesswork.
Work directly with the product owner to turn platform direction into a sequenced roadmap with measurable outcomes.
Develop lightweight prototypes to help guide engineering teams in building solutions that meet user needs.
Run product discovery through research, prototyping, and pilots.
Run delivery from MVP through scale.
Manage scope, tradeoffs, and dependencies across engineering, data, and design.
Build and maintain a use-case catalog with prioritization based on value, feasibility, risk, and readiness.
Prioritize features based on user value, technical dependencies, and cost.
Partner with engineers and contractors to plan, ship, and improve the product.
Maintain backlog quality, run sprint planning, track progress, and align stakeholders through clear decision points.
Define and enforce human-in-the-loop checkpoints at critical stages of AI-driven workflows to ensure output quality, risk mitigation, and user trust.
Design how AI-augmented reporting, insights, and recommendations are embedded into existing team workflows.
Define the interaction model for dashboards, KPIs, and natural language interfaces, prioritizing adoption and speed-to-insight.
Shape agent and LLM capabilities, including reasoning, tool use, human-in-the-loop workflows, and exception handling.
Ensure LLM experiences are grounded in trusted, governed business data and tied to real use cases, including AI recommendation engine outputs.
Define and evolve the data layer that governs how business metrics and market signals are modeled, accessed, and surfaced across AI products and natural language interfaces.
Drive requirements for data connectors, access patterns, security, privacy, and logging/auditability.
Define how the product integrates with enterprise systems, identity, and role-based access controls.
Ensure data pipelines feeding the product are reliable, governed, and observable.
Serve as the connective tissue between cross-functional business teams and engineering.
Synthesize feedback, leader input, and operational signals into prioritized backlog items that keep the product grounded in how people actually work.

Requirements

What you’ll need

8+ years of experience across product management, software engineering, data engineering, or related technical roles.
2+ years of product management experience with direct ownership of PRDs, roadmaps, user stories, and feature prioritization.
Bachelor's degree in CS or a related technical field, or equivalent hands-on experience in full-stack software engineering or software development.
Strong understanding of backend systems, APIs, service architecture, data modeling, and modern application design.
Experience working with structured data platforms, semantic layers, data pipelines, and cloud-based data systems.
Working knowledge of SQL and strong technical fluency in how data moves from source systems into user-facing product experiences.
Experience building or supporting products that use AI or LLM capabilities in production.
Ability to write requirements that engineers trust and can execute without guesswork.
Willingness to move fast, iterate aggressively, fail, rebuild, and improve the product through repeated cycles of learning.
Strong judgment in balancing technical constraints, business needs, and user experience.
Strong organizational and communication skills, able to keep multiple workstreams moving, align cross-functional teams, and communicate clearly across technical and non-technical audiences.
Prior experience as a conduit between external partners and internal product teams, comfortable synthesizing feedback into actionable product input.
Experience building platform products, internal tools, data products, or AI-enabled enterprise applications.
Experience with products that combine metric layers, semantic data layers, dashboards, and natural language interfaces.
Background in software engineering or data engineering before moving into product management.
Experience working with modern data platforms such as Snowflake, Databricks, or similar environments.
Experience in environments that value rapid iteration, strong product instincts, and close collaboration between product and engineering.
Familiarity with telecom, subscription businesses, or other KPI-heavy operating environments is a plus.
Experience working with or alongside AI governance, compliance, or responsible AI teams.

Benefits

Comp & perks

Medical/Dental/Vision coverage
401(k) plan
Tuition reimbursement program
Paid Time Off and Holidays (based on date of hire, at least 23 days of vacation each year and 9 company-designated holidays)
Paid Parental Leave
Paid Caregiver Leave
Additional sick leave beyond what state and local law require may be available but is unprotected
Adoption Reimbursement
Disability Benefits (short term and long term)
Life and Accidental Death Insurance
Supplemental benefit programs: critical illness/accident hospital indemnity/group legal
Employee Assistance Programs (EAP)
Extensive employee wellness programs
Employee discounts up to 50% off on eligible AT&T mobility plans and accessories, AT&T internet (and fiber where available) and AT&T phone

ATS Keywords

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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

product managementPRDsuser storiesfeature prioritizationbackend systemsAPIsdata modelingSQLAI capabilitiesdata pipelines

Soft Skills

organizational skillscommunication skillsjudgmentsynthesizing feedbackcross-functional collaborationiterative improvementbalancing technical constraintsuser experience focusdecision makingstakeholder alignment

Certifications

Bachelor's degree in Computer Scienceequivalent hands-on experience in software engineering