Full Stack Commerce Engineer (generative AI/ML) - Consultant

As a Full Stack Commerce Engineer (Consultant), you will support the design and delivery of AI enabled commerce and experience solutions, working closely with senior architects, managers, and client stakeholders.

• Support Client Facing Engagements: Support client workshops and engagements by acting as a technical contributor, helping design use cases and platform solutions that apply Generative AI to real business challenges, under the guidance of senior technical leads.
• Build AI Powered Solutions: Contribute to the design and development of full stack solutions from prototype through to production, including agentic workflows in Python and integrations with LLMs such as OpenAI/ChatGPT, Google Gemini, Nvidia, and Writer.
• Work Across the Commerce Ecosystem: Support the integration of AI/ML capabilities with enterprise platforms, helping connect data and services across Commerce, PXM, CDP, DAM, CMS, and CRM systems.
• Develop and Maintain Data Solutions: Design and implement database components using SQL and NoSQL technologies, supporting data pipelines and stored procedures that handle large scale commerce and customer data.
• Contribute to Delivery & Engineering Excellence: Collaborate within agile delivery teams, contributing to solution design, development best practices, and DevSecOps processes, while learning from senior engineers and architects across the Accenture Data & AI community.

• Experience in a client facing or forward deployed engineering role, supporting the translation of business requirements into technical solutions.
• Strong full stack engineering experience, with Python used for AI/ML or data driven applications.
• Hands on experience building and deploying applications on cloud platforms (Azure or GCP preferred), including security, networking, storage and monitoring.
• Practical experience integrating Generative AI services (e.g. OpenAI API, Vertex AI, Azure ML) and familiarity with core AI/ML patterns such as RAG and deployment architectures.
• Understanding of how AI/ML integrates with enterprise experience platforms (Commerce engines, DAM, PXM, CDP, CMS, CRM).
• Solid skills in SQL and NoSQL databases, including writing and maintaining stored procedures.
• Foundation in modern software engineering and DevSecOps practices.

• Cloud certifications (e.g. Azure Solutions Architect, Google Professional Cloud Architect).
• Exposure to MLOps frameworks and vector databases (e.g. Pinecone, Weaviate).
• Experience contributing to proof of concepts or MVPs, demonstrating rapid learning and experimentation.
• Experience supporting production AI/ML solutions, ideally within retail or CPG environments.

London

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