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Agentic Commerce Engineering Specialist | Communications, Media, & Technology

AI Native Software Engineering Team Lead/Consultant | Mid-Level | Full time
Job No. R00366055 | Multiple Locations
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About Accenture Song – Customer Technology, Commerce

Accenture Song accelerates growth and value for our clients by combining creativity, technology, and data-driven intelligence. Within Song, the Customer Technology – Commerce practice helps organizations design, build, and scale modern digital commerce ecosystems that deliver personalized, seamless, and intelligent customer experiences.

We integrate commerce platforms, customer data, marketing technology, and AI-powered decisioning to transform how brands engage customers across channels. By embedding Generative AI and Agentic AI into commerce operations, we enable real-time personalization, autonomous merchandising, dynamic pricing, campaign orchestration, and revenue growth at scale.

What’s in it for you

  • Build Agentic Commerce capabilities where Agentic AI is embedded into real-world platforms (Salesforce, Adobe, SAP, composable/MACH stacks)
  • Contribute to Accenture Song’s Agentic Commerce accelerators and reusable assets
  • Help deliver solution components—from build through rollout and value realization
  • Work with global clients across B2C, B2B, and B2B2C commerce
  • Grow your engineering expertise across AI, backend, cloud, and commerce platforms, with mentorship from senior leaders

What you will do in this role

As a Consultant in Customer Technology – Commerce, you will build and support Agentic Commerce capabilities—developing AI-driven features that are production-ready, secure, and integrated with enterprise commerce ecosystems—working under the direction of Managers and Senior Managers.

Commerce & Platform Delivery

  • Implement Agentic Commerce features using established architecture patterns across composable and platform-led commerce
  • Configure and develop on Salesforce, Adobe, SAP, and MACH ecosystems in line with solution designs
  • Support prototype-to-production efforts, helping embed agentic workflows into live commerce environments

Engineering & Build

  • Develop modular, reusable agent components integrated with commerce engines, APIs, and backend services
  • Follow enterprise-grade standards for scalability, security, observability, and reliability of agentic systems
  • Implement integrations with LLM platforms, orchestration frameworks, and vector stores under guidance

Delivery & Execution

  • Contribute to engineering pods across AI, backend, data, cloud, and DevOps
  • Support CI/CD pipelines, cloud-native deployments, and containerized workloads on Azure, AWS, or GCP
  • Build and test integrations with CRM, CDP, payments, order management, pricing, and fulfillment systems

Quality, Governance & Value

  • Apply governance, compliance, auditability, and explainability requirements within build work
  • Instrument and report technical KPIs for agent performance and reliability
  • Support human-in-the-loop and feedback mechanisms that improve agent effectiveness

Growth & Collaboration

  • Contribute to internal accelerators, reference components, and technical documentation
  • Collaborate with client and team working-level stakeholders to deliver features
  • Continuously build skills across commerce platforms and agentic AI, and mentor junior team members

Basic Qualifications

  • 3+ years of experience building commerce or digital platform solutions with hands-on experience developing on at least one enterprise commerce platform (Salesforce Commerce, Adobe Commerce, SAP Commerce, or composable/MACH stacks) with exposure to agentic AI or Generative AI features integrated into applications
  • Working knowledge of API-led, microservices-based architectures
  • 1+ year of experience working in the CMT Industry.

Preferred Qualifications

  • Familiarity with LLMs, RAG pipelines, or vector databases is a plus
  • Experience contributing to delivery using CI/CD, cloud-native architecture, and DevOps practices
  • Awareness of governance considerations for AI-driven systems
  • Understanding of observability and testing fundamentals
  • Ability to work effectively within cross-functional engineering teams
  • Clear communication skills—able to explain technical work to team members and stakeholders
  • Eagerness to learn, grow expertise, and support junior team members




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