Overview In this hybrid role, you will design end-to-end AI-enabled marketing architectures that boost productivity and reduce costs. You collaborate across AI, data engineering, IT, and vendors to embed AI into marketing workflows while ensuring governance and enterprise alignment. You'll translate business needs into scalable, secure solutions and guide vendor evaluations and build-versus-buy decisions. This position offers exposure to cutting-edge MarTech and a chance to shape AI-enabled marketing at scale.
Compensation / Benefits- health & wellbeing benefits
- career development programs
- inclusive work environment
- flexible/hybrid workplace
- industry-leading benefits
Responsibilities- Assess current marketing workflows, data flows, and dependencies to identify automation opportunities
- Map end-to-end marketing and communications processes and pinpoint bottlenecks
- Define AI-embedded architectures aligning with business requirements and enterprise standards
- Maintain knowledge of AI tools (LLMs, retrieval-augmented generation, recommendation engines) for governance alignment
- Lead onboarding/integration of AI agents and applications into the MarTech stack, including vendor evaluation
- Review data pipelines with Data Engineering for efficient data flow and governance
- Specify infra requirements (model hosting, vector stores, orchestration, monitoring) and performance targets
- Conduct vendor due diligence and advise on build-vs-buy decisions
- Ensure security, privacy, and compliance across AI solutions
- Collaborate with cross-functional teams and represent marketing in EA reviews
- Oversee governance and risk management related to AI deployments
Key requirements- Bachelor in Computer Science, Software Engineering or related field
- Experience in enterprise architecture and AI solution design
- Knowledge of LLMs, generative AI, retrieval-augmented generation, and AI workflow orchestration
- Familiarity with cloud platforms (Azure, AWS, GCP) and AI infrastructure
- Experience with API design, data governance, and data integration standards
- Understanding of security, privacy, and compliance in AI projects
- Strong communication skills for non-technical stakeholders and cross-functional influence
- Project and requirements management skills
- Vendor evaluation and due diligence experience
- Certifications in cloud platforms or EA frameworks are advantageous
- strong communication
- stakeholder management
- cross-functional collaboration
- LLMs
- retrieval-augmented generation
- recommendation engines
