Project Role : Custom Software Engineer

Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.

Adobe Experience Platform (AEP)

Minimum 3 Year(s) Of Experience Is Required

Educational Qualification : 15 years full time education

As an AEP AI-Native Developer, the requirement is to design, build, and configure Adobe Experience Platform solutions — spanning data ingestion, schema design, segmentation, Real-Time CDP, and journey orchestration — with AI embedded as a core part of the work. Focus primarily on hands-on AEP development and requirement analysis, contributing directly to the delivery of scalable, data-driven customer experience solutions for enterprise clients.

Leverage AI coding assistants and LLM APIs daily to accelerate platform configuration, data modelling, query optimization, and integration tasks — while applying engineering judgement to validate every AI-generated output before it reaches production.

Requirement Analysis & Solution Design: Analyze business and data requirements using AI tools to synthesize briefs, identify data gaps, and draft AEP solution specifications — then validate the output in collaboration with architects and senior stakeholders

Schema, Data Modelling & Ingestion: Design and implement XDM schemas, dataset configurations, and data ingestion pipelines (batch and streaming) use AI to accelerate schema modelling, identify mapping patterns, and validate data integrity across sources

Segmentation & Real-Time CDP: Build and configure audience segments, merge policies, and identity graph settings within Real-Time CDP leverage AI to generate segment logic proposals and validate audience definitions against business requirements

Design and configure customer journeys in Adobe Journey Optimizer — including triggers, conditions, actions,



and message personalization use AI tools to accelerate journey logic drafting and test scenario generation

Develop and maintain AEP API integrations and Query Service SQL workloads use AI-assisted code generation and debugging to accelerate integration delivery and optimize query performance

AI Output Quality & Prompt Engineering: Validate all AI-generated AEP configurations, code, and data models before they reach production develop and contribute AEP-specific prompt engineering patterns — for schema generation, segment queries, journey logic, and API integration — to shared team libraries

Data Quality & Governance: Implement and maintain data quality rules, consent management configurations, and data governance policies within AEP use AI to identify anomalies, surface data quality issues, and propose remediation

Monitoring & Troubleshooting: Monitor AEP data pipelines, ingestion jobs, and journey executions apply AI-assisted diagnostics to root-cause failures and performance issues document findings and resolution steps clearly

AEP Core: Proficiency in Adobe Experience Platform — XDM schema design, dataset management, identity resolution, and Real-Time CDP configuration

Data Ingestion & Pipelines: Hands-on experience with AEP batch and streaming data ingestion, source connectors, and data flow configuration

Experience building audience segments, merge policies, and identity graph configurations in Real-Time CDP

Adobe Journey Optimizer (AJO): Working knowledge of AJO journey design, triggers, conditions, message personalization, and campaign configuration

AEP Query Service:



Proficiency in AEP Query Service — SQL-based data exploration, dataset analysis, and query optimization

Experience with AEP APIs (Profile, Segmentation, Data Ingestion, Flow Service) and RESTful API integration patterns

AI-Assisted Development: Demonstrated hands-on use of AI coding assistants (GitHub Copilot, Claude) integrated into daily AEP development — with practical examples of AI-driven schema generation, query optimization, or integration acceleration

LLM API Integration: Experience calling LLM APIs (OpenAI, Anthropic, or similar) in application code, with understanding of token management, latency, and cost trade-offs

Data Governance & Privacy: Familiarity with AEP data governance frameworks, consent management, and DULE (Data Usage Labelling and Enforcement) policies

Cloud & DevOps: Familiarity with cloud fundamentals (AWS, Azure, or GCP) and CI/CD pipeline concepts

Programming Languages: Proficiency in SQL and JavaScript working knowledge of Python a plus

Experience with AEP Destinations — configuring data export to advertising, analytics, and marketing platforms

Familiarity with Customer AI and Attribution AI within AEP's Intelligent Services

Exposure to agentic system concepts — awareness of orchestration frameworks (LangChain, LangGraph) and RAG pipelines, and how AEP data layers connect to AI agent architectures

Experience with Adobe Analytics integration and data migration to AEP

Understanding of CDP architecture patterns and enterprise data platform design

Bachelor's degree in Computer Science, Computer Engineering, Data Engineering, Software Engineering, or a related field

4+ years of commercial AEP development experience in production environments

Demonstrated experience with Adobe Journey Optimizer (AJO) in a delivery context

Ability to validate, evaluate, and improve AI-generated outputs understanding of AI limitations and responsible use

A 15-year full time education background is required

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