Marketing AI Workflow Architect (Houston, TX)

Marketing AI Workflow Architect (Houston, TX)

  

This role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week from an HPE office.

Job Description:

   

HPE is seeking a technically proficient, business-savvy AI Solutions Architect with a deep understanding of marketing operations, workflows, and data flows. This individual will be responsible for analyzing existing marketing processes, identifying opportunities for AI integration, and designing end-to-end AI-enabled architectures that enhance productivity and reduce costs. The AI Solution Architect will collaborate closely with AI/ML engineering teams, data engineering, IT, and third-party vendors to develop secure, compliant, and scalable AI solutions aligned with organizational objectives

LOCATION:   This is an onsite position in either HPE’s Houston, TX. campus on a hybrid schedule of up to 3 days per week in office.

      

KEY RESPONSIBILITIES:

Business & Process Analysis

• Conduct comprehensive assessments of current marketing workflows, including cross-team handoffs, operational dependencies, and data flows.
• Map end-to-end marketing and communications processes, identifying bottlenecks, redundancies, and automation opportunities.
• Understand the data landscape, including sources, quality, and integration points, to inform AI embedding strategies.

AI Architecture Alignment & Integration

• Work closely with the engineering-side AI architecture team to understand the to-be AI architecture and how manual or semi-automated marketing processes are being transformed into intelligent, automated solutions — ensuring marketing's business requirements and enterprise-alignment needs are reflected in that design.
• Maintain a strong working knowledge of the AI solutions being built (LLMs, retrieval-augmented generation, recommendation engines, and other generative AI tools) so enterprise standards, governance, and platform requirements can be mapped onto them — without duplicating the build-side design and development work.
• Drive the onboarding and integration of AI agents, tools and applications onto the MarTech stack to enable business processes — spanning both in-house solutions and third-party/bought AI, where this role leads vendor evaluation, build-vs-buy, and enterprise-compliant integration.
• Review and pressure-test architecture artifacts (context diagrams, data flow diagrams, interface specifications, solution blueprints) produced by the data science and engineering teams — validating enterprise fit, integration, and governance rather than authoring them.

Workflow & Data Streamlining

• Collaborate with Data Engineering teams to design data pipelines that facilitate efficient, low-overhead data flow into and out of AI applications, avoiding unnecessary complexity.
• Ensure data governance, security, and privacy are embedded into all AI solutions.
• Identify and specify API and integration requirements for AI agents, ensuring interoperability within the broader MarTech ecosystem and with third-party AI vendors.

Technology Stack & Platform Enablement

• Work with IT, platform engineering, and AI teams to specify infrastructure needs, including model hosting, vector stores, storage, orchestration, and monitoring tools.
• Define and specify performance requirements such as latency, throughput, availability, and resilience for AI services.
• Influence platform roadmaps and identify gaps in infrastructure or tooling that could hinder AI deployment at scale.

Vendor & Build vs. Buy Strategies

• Lead vendor evaluations, pe