Director of Engineering - Decision Intelligence Platform

This position requires office presence of a minimum of 5 days per week and is only located in the location(s) posted. Relocation is offered.

Director of Engineering – Decision Intelligence Platform

About AT&T:

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.

About the Team and the Role:

The Platform Engineering team within the Consumer Technology eXperience (CTX) organization delivers reliable, scalable, and high-performance platforms and solutions across omnichannel. We adapt to customers' evolving needs by adhering to industry best practices, continuously enhancing our offerings, and embracing innovative technologies.

The Director of Engineering – Decision Intelligence Platform will lead the strategy, architecture, build, and scaling of an AI/ML-driven Decision Intelligence platform that powers enterprise decisioning (Next Best Action/Next Best Offer), journey management, and real-time personalization across digital and assisted channels. This leader will be accountable for establishing a robust data-and-model foundation (streaming + batch), a reusable decisioning layer, and low-latency activation services that translate customer signals into context-aware experiences in milliseconds.

The ideal candidate will have a proven track record of managing high-performing engineering teams, driving innovation, and delivering scalable solutions that enhance marketing effectiveness and operational efficiency.

What You’ll Do

Strategic Planning & Vision

• Set vision and roadmap for an AI/ML-driven Decision Intelligence platform enabling NBA/NBO, journey orchestration, and real-time personalization across channels.

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• Partner with Marketing, Product, Analytics, and Business leaders to prioritize high-impact use cases and deliver measurable outcomes (uplift, conversion, churn, CLV, cost-to-serve).
• Define the reference architecture across event streaming, identity, feature store, MLOps, decision services, and activation—optimized for low latency, scale, governance, and explainability.
• Evaluate and adopt new capabilities (real-time inference, bandits/experimentation, privacy-enhancing techniques) based on business value and operational readiness.

Team Leadership & Development

• Build and lead a high-performing org across software, data, ML, and analytics; drive a platform culture of reusable components, productized APIs, self-service tooling, and operational excellence.
• Drive execution via clear OKRs, prioritization, dependency management, and cross-functional operating rhythms with MarTech, IT, Governance, Security, and channel teams.

Technical Implementation, Delivery & Optimization

• Deliver core platform capabilities: batch/streaming pipelines, real-time signals ingestion, identity/profile, feature pipelines (online/offline parity), model serving and monitoring (drift), decision engine (models + rules + constraints), and orchestration/activation integrations.
• Integrate with enterprise systems (CRM/CDP/CMS/commerce/data platforms) using API-first and event-driven patterns.
• Implement closed-loop measurement and optimization through experimentation, performance reporting, and feedback pipelines to continuously improve decision policies and models.
• Own reliability and compliance: privacy-by-design, data integrity, auditability, observability, CI/CD, SRE practices, and 24x7 SLAs/SLOs (incident response, runbooks, resilience testing).

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What You’ll Bring

Experience & Background

• 15+ years in technology, including 8+ years leading cross-functional teams across engineering, data, and ML for customer-facing platforms.
• 10+ years building cloud-scale data platforms (lake/warehouse, ETL/ELT, streaming).
• Proven integration with MarTech/CDP/journey orchestration and activation ecosystems (Adobe/Salesforce/Marketo/HubSpot or similar), focused on real-time activation and personalization.
• End-to-end ownership of platform architecture through production operations, including governance and lifecycle management.

Leadership & Strategic Skills

• Strong record of building high-performing teams (including managers of managers) and aligning business and technical stakeholders.
• Product/platform mindset with disciplined prioritization to drive adoption and measurable customer outcomes.
• Clear communicator who can explain NBA/NBO, experimentation, and model risk to non-technical audiences.

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• Ability to manage competing priorities while maintaining quality, security, and reliability.

Technical Skills & Proficiency

• Expertise in cloud-scale distributed systems and low-latency, high-throughput real-time decisioning (API-first, event-driven architectures; Azure/AWS/GCP).
• Hands-on experience with key stack components:
• Adobe Experience Platform (AEP) (RT-CDP, AJO, Target, CJA)
• Streaming (Kafka, Flink, Spark or equivalent)
• Data platforms (Snowflake/lakehouse), strong SQL and NoSQL
• Microservices (Java/Node), Kubernetes, API gateway/service mesh patterns
• Observability & reliability (logs/metrics/traces, alerting, SLO/SLA management)
• Deep understanding of Decision Intelligence patterns: NBA/NBO, orchestration, eligibility/constraints, frequency capping, and omnichannel policy consistency.
• Proven production ML delivery: feature engineering, feature store parity, model building, model serving, MLOps, monitoring/drift, retraining, and experimentation (A/B, uplift; bandits where appropriate).
• Strong modern engineering practices: Agile/SAFe, DevOps/MLOps, CI/CD, IaC, secure-by-design, and automated testing for data/ML/decision logic.
• Experience using AI coding assistants to accelerate delivery while maintaining code quality and ownership.
• Ability to build measurement and reporting for decision performance (KPIs, funnels, offer/model performance, closed-loop feedback).