S&C Global Network - AI - Song - CDP-Consultant

Overview

Build and operate custom CDPs and agentic AI solutions on GCP for marketing analytics.

Key Responsibilities

• ai architecture
• prompt engineering
• data pipelines
• cdp design
• mlops
• governance

Tasks

-Conduct stakeholder interviews and gather business requirements -Provide deep domain expertise in our client’s business and broad knowledge of digital marketing together with a Marketing Strategist industry -Work with Business Analysts, Data Architects, Technical Architects, DBAs to achieve project objectives - delivery dates, quality objectives etc. -Architect the core interaction logic and decision-making frameworks for enterprise-grade, agentic AI systems within marketing on GCP. -Create insights presentations and client-ready decks, effectively communicating findings and recommendations. -Implement robust monitoring, logging, and observability specifically for the performance, decision paths, and output quality of agentic AI systems. -Design and implement data storage strategies (Datastores) optimized for efficient retrieval of context for AI agents. -Provide hands-on support and platform training for our clients. -Coordinate with website developers for Analytics integration, datalayer implementation, Martech tools integration -Prototype new approaches and provide expert guidance on GCP AI services, Gemini, RAG, advanced prompting, and reasoning AI techniques. -Develop and apply advanced prompting techniques (e.g., Chain-of-Thought, Few-Shot) to guide and enhance the reasoning, accuracy, and output quality of AI agents. -Develop and deploy AI-driven solutions for generating multimodal marketing assets (e.g., personalized images, video snippets, audio messages) powered by Gemini. -Assess and audit the current state of a client’s marketing technology stack (MarTech) including data infrastructure, ad platforms and data security policies together with a solutions architect. -Model for Insight & Activation: Design and implement data models in BigQuery optimized for customer identity resolution, 360-degree profile creation, segmentation, and analytics. -Translate business requirements into BRDs, CDP customer analytics use cases, structure technical solution -Advance prompt engineering (e.g., Chain-of-Thought, ReAct) to optimize LLM reasoning. -Implement and leverage grounding & evaluation capabilities within Agentic AI systems to ensure outputs are factually accurate, contextually relevant, and traceable to specific data sources for marketing applications. -Implement LLMops best practices for the lifecycle management of agentic AI models, including CI/CD for AI components. -Champion DevOps & MLOps: Champion and implement Infrastructure as Code (IaC) using Terraform. Build CI/CD pipelines using Cloud Build to automate testing and deployment, manage container images in Artifact Registry, and secure credentials using Google Secret Manager. -Ensure Governance & Security: Implement solutions that adhere to data governance best practices and privacy regulations (e.g., GDPR, CCPA), ensuring data is handled securely and ethically. -Create a strategic CDP roadmap focused on data driven marketing activation. -Architect & Design: Lead the technical design and architecture of enterprise-grade, custom CDPs and marketing data warehouses on Google Cloud Platform (GCP). -Work with the Solution Architect to strategize, architect, and document a scalable CDP/Martech implementation, tailored to the client’s needs. Able to integrate multiple Martech tools. -Mentor and guide junior resources, fostering a collaborative and growth-oriented team environment. -Design and Implement Adobe Stack Martech tools like Adobe Target, Adobe Campaign, Adobe Journey Optimizer, Adobe Launch, Adobe Web SDK, Adobe Analytics, Customer Journey Analytics -Ensure analytics are consistently implemented across digital properties. Diagnose and troubleshoot analytics/Martech implementation and platform configuration issues. Perform end-to-end QA testing for integrations. -Leverage Gemini models' reasoning capabilities to enable agents for complex analysis, strategic planning, and problem-solving in marketing contexts. -Build Production-Grade Data Pipelines: Engineer robust, scalable, and automated data pipelines for both streaming and batch ingestion using services like Cloud Dataflow, Pub/Sub, and Cloud Functions. Containerize processing jobs with Docker for portability and scalability. -Leverage Google Agent Development Kit (ADKs) and APIs to orchestrate complex, multi-step agentic workflows, focusing on reasoning capabilities. -Collaborate & Innovate: Work within a multi-disciplinary team to translate business requirements into technical solutions, prototype new approaches, and provide expert guidance on the art of the possible with GCP and modern data engineering. -Perform technical analysis & design for Martech related initiatives. Define requirements for Martech implementation/reporting dashboard. -Develop strong relationships with clients at all levels, understanding their specific challenges and opportunities. -Ensure secure and compliant interactions for AI agents, managing credentials and secrets relevant to AI model access. -Design, implement, and optimize Retrieval Augmented Generation (RAG) pipelines to equip Gemini agents with contextually relevant information from various knowledge sources. -Deploy & Serve: Develop and deploy containerized, serverless APIs (using Docker and Cloud Run) for real-time data ingestion and activation, feeding customer segments and triggers into marketing platforms. -Design agentic AI systems for scalability, robustness, and real-time responsiveness in autonomous marketing decision-making. -Prioritize CDP use cases together with the client. -Operationalize Machine Learning: Collaborate with data scientists to productionize ML models (e.g., propensity, LTV, segmentation) using the Vertex AI platform. Build automated training pipelines, and deploy models for real-time inference.

Requirements

• google gemini
• terraform
• python
• vertex ai
• adobe rtcdp
• gcp

What You Bring

-Hands-on experience working with Google Gemini models and their APIs/SDKs is highly preferred. -Adobe Journey Optimizer or/and Adobe Campaign -Deep domain expertise in Tag Management, Journey Orchestration, Campaign Management, A/B Testing -DevOps & Automation Mindset: Strong experience with Terraform for infrastructure provisioning and CI/CD tools (Cloud Build, Jenkins, GitLab CI). -Strong hands-on with advanced JavaScript and jQuery. Able to develop custom tags/scripts using tag managers -Deep developer expertise for Journey Orchestration and Personalization tools like Adobe Target, Adobe Campaign, Adobe Journey Optimizer -Deep GCP Expertise: Hands-on experience with key GCP data services: BigQuery, BigTable, Vertex AI, Dataflow, Pub/Sub, Composer (Airflow), Cloud Functions, Cloud schedular and GKE. -Advance level Python, SQL, Shell Scripting experience -At least 2+ years of relevant work experience in marketing, consulting, or analytics -2+ years of hands-on experience in software engineering with a data focus, or AI/ML engineering. -Experience with Vertex AI RAG Engine and GCP datastore. -Adobe RTCDP (AEP) developer and any other CDP platforms experience e.g., Lytics CDP platform developer, or/and Segment CDP platform developer, or/and Tealium CDP platform developer, or/and Salesforce CDP platform developer, or/and Custom CDP developer on any cloud -Deep expert level knowledge of paid media destinations - Google Ads, DV360, Campaign Manager, Facebook Ads Manager, The Trading desk etc. -Google Ads, DV360, Campaign Manager, Facebook Ads Manager, The Trading desk etc. -Advanced proficiency in Python is mandatory. -Be a platform expert in Adobe RTCDP (Adobe Real time CDP). Developer level expertise on Adobe RTCDP (Adobe Experience Platform) is a must with other CDP platforms like Lytics, Segment, Amperity, Tealium, Treasure Data etc. including custom build CDPs as an added advantage -Containerization & Serverless Deployment: Hands-on experience with Docker, managing images in Artifact Registry, and deploying applications to Cloud Run or GKE. -Experience with Adobe Marketing Cloud tools like Adobe Workfront, Adobe Experience Manager (AEM), DAM is a plus -At least 2+ years of experience working in an agency environment -Demonstrate strong communication skills, both verbal and written, to effectively convey complex concepts and insights to stakeholders. -Exceptional problem-solving and analytical capabilities, particularly in understanding and applying reasoning to complex problems. -Experience working with Multimodal LLM’s. Preferably Gemini. -Good communication skills -Experience using GCP Evaluation and Grounding SDK. -Proficient in Terraform, CI/CD practices (Cloud Build), Docker, Artifact Registry, and Google Secret Manager. -Experience on using Agent Development Kit(Adk) -Experience on debuggers like Adobe Launch debugger, Omnibug, Charles, Browser stack, etc. -MLOps Experience: Familiarity with deploying and managing models using Vertex AI (or similar platforms like SageMaker/MLflow) is a strong advantage. -Deep expert level knowledge of reporting tools like GA360/GA4, Adobe Analytics, Customer Journey Analytics -Hands-on experience with Retrieval Augmented Generation (RAG) pipelines and integrating external knowledge sources for LLMs. -Experience integrating with key marketing platform APIs is highly advantageous. -Business intelligence expertise for insights, actionable recommendations. -Experience working with large language models (LLMs) with a focus on their reasoning capabilities. -Advance level JavaScript /jQuery -Familiarity with frameworks like Agent Development Kit (ADK) for building LLM applications and agentic workflows. -Graph database understanding for solving advance use cases – e.g. Identity resolution -Experience working on Vertex AI Rag engine and GCP datastores. -GA4/GA360, or/and Adobe Analytics, or/and Customer Journey Analytics(CJA) -Deep developer level expertise for real time event tracking for web analytics e.g., Google Tag Manager, Adobe Launch, Adobe Web SDK, etc. -At least 2 years of demonstrable experience building and managing data/AI solutions on Google Cloud Platform (GCP). -Marketing Domain Acumen: Understanding of core marketing concepts like identity resolution, customer segmentation, and audience activation. Experience integrating with marketing platform APIs is highly desirable. Experience with google cloud integration connector is a plus -Google Tag Manager, and/or Adobe Launch/AEP Web SDK, and/or Tealium iQ – any and/or any Tag Manager Tool - any one (prefer whoever has any one of these) -Security Best Practices: Experience using tools like Google Secret Manager or HashiCorp Vault to manage application secrets. -A collaborative spirit and the capacity to mentor and guide junior team members. -Experience in Postman APIs is a plus -Project management expertise for sprint planning -Data processing, data engineer and data schema/models expertise for CDPs to work on data models, unification logic etc. -Data Migration, DevOps, MLOps, Terraform Script programmer -Direct experience building or contributing to a custom Customer Data Platform (CDP) or a similar customer-centric data system. -Experience working and designing Agentic AI systems for complex reasoning and multi-step task. -At least 2+ years of relevant work experience of implementing CDP solutions with deep understanding of identity resolution methods with minimum 1 year in Adobe RTCDP -Demonstrable experience building and deploying agentic AI systems, leveraging LLMs for complex decision-making. -Outstanding communication and stakeholder management skills. -Adobe Target and/or Optimizely or any personalization or A/B testing tool -Adobe Marketing Cloud - Adobe Workfront, Adobe Experience Manager (AEM), DAM -Google Cloud Professional Machine Learning Engineer (PMLE) certification is highly desired. -Experience in deploying and managing AI models in production environments using Vertex AI. -At least 2 years of experience working as Subject matter expert in Adobe Marketing Cloud Stack -Experience with Campaign Management tools like Adobe Journey Optimizer or/and Adobe Campaign is a plus. -Deep Cloud experience (GCP, AWS, Azure) -Strong problem solving skills -Experience with A/B testing tools like Adobe Target is a plus. -Basic HTML -In-depth, hands-on expertise with core GCP data and AI services, including Vertex AI (for LLM integration, prompt engineering, RAG pipeline development). -Proven ability to apply advanced prompting techniques (e.g., Chain-of-Thought, Few-Shot) to guide and enhance LLM reasoning and output quality. -Modern Data Stack Knowledge: Experience with tools like dbt (Data Build Tool) for data transformation is a significant plus.

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