Jobs at dentsu

Lead design and development of scalable cloud data platforms and ETL/ELT pipelines across AWS/Azure/GCP. Build and optimize data warehouses/lakehouses, implement MDM and governance, support analytics/BI, mentor junior engineers, and contribute to presales PoCs and solution designs.

Lead technical design and implementation of Salesforce Data Cloud and MCP personalization solutions. Architect data models and ingestion pipelines, enable identity resolution and audience activation, integrate MarTech systems, ensure data quality and privacy compliance, troubleshoot integrations, mentor engineers, and support journey orchestration and roadmap planning for real-time personalized experiences.

Conduct industry and company research, produce detailed and customized research reports, support new-business pitches, interface with stakeholders, track research tools and trends, and translate data into actionable insights and presentations to inform strategy.

Lead end-to-end delivery of Qualtrics Engage programs, acting as SPOC for clients and stakeholders. Manage integrated project plans, budgets, risks, RAIDD, change control, resources, QA/UAT, and launch. Establish governance, run kickoffs and status meetings, oversee survey/dashboard/workflow builds, ensure sign-offs, and transition to managed services. Support business case and benefits tracking. Qualtrics certification is a plus.

Design, build, and maintain Magnolia CMS modules and headless content APIs; develop responsive frontend experiences; integrate Magnolia with Salesforce Commerce Cloud; implement CI/CD; ensure performance, security, and testing; mentor developers and contribute to architecture.

Lead architecture and engineering for multi-agent LLM systems: design orchestration, build reusable agent components, set CI/CD and deployment standards, evaluate LLM providers, mentor senior engineers, and produce operational runbooks and documentation for agentic AI deployments.

Lead solution architecture and delivery across Salesforce Sales Cloud, Service Cloud, Data Cloud, and Agentforce. Design ingestion, identity resolution, Calculated Insights, segmentation and activations. Architect CPQ, case management, Omni-Channel, and Agentforce agents. Mentor engineers, produce SDDs and integration designs, present trade-offs to stakeholders, and govern data quality, reconciliation, and analytics integration with Power BI/Tableau. Support Marketing Cloud connector and deployment patterns where required.

Execute case studies, graphics and slide production; perform editorial QA, research and competitive analyses; deliver standard reports and intelligence-supported pitch materials; build automated processes under manager guidance; lead team members to meet SLAs and global multi-market project requirements.

Lead technical architecture and hands-on development for multi-agent and LLM orchestration systems. Set engineering standards, build reusable agent components, manage CI/CD and MLOps, evaluate LLM providers, mentor engineers, collaborate on cross-timezone architecture, and produce operational documentation for agentic AI deployments across multiple client implementations.

The Braze Development Manager leads software engineering teams, providing technical guidance while overseeing implementation, design, and delivery of marketing automation solutions using Braze.

Lead design and delivery of enterprise-scale Salesforce solutions, specializing in Financial Services Cloud, Data Cloud and Agentforce. Define end-to-end architecture, run discovery and workshops, guide integrations, ensure scalability, security and governance, support pre-sales, mentor developers, and oversee implementation and code quality.

Lead and scale a P&L-backed analytics/AI practice delivering GenAI solutions (LLMs, orchestration, model integration) for marketing, creative, media, and commerce. Sell, design, deliver, and operationalize production AI systems, collaborate with creative and media teams, and drive business outcomes. Preferred experience with modern AI/data stacks (GCP, BigQuery, Vertex AI). Based in Bengaluru.

Lead development of generative and multimodal AI systems: design agentic workflows, build and fine-tune transformer models, implement hybrid retrieval and knowledge-graph solutions, deploy scalable model APIs on cloud, collaborate with cross-functional teams, and mentor junior engineers.

Lead design and delivery of Salesforce B2B Commerce Cloud solutions including account hierarchies, quotes-to-order, contract pricing, ERP/CRM integrations, and LWC storefronts. Mentor developers, own CI/CD and release strategy, manage multi-market rollouts, troubleshoot escalations, and ensure scalable, secure enterprise eCommerce implementations.

As a Senior Web Stack Engineer, you'll deliver high-quality frontend solutions, ensuring performance, accessibility, usability, and security across headless architectures while mentoring developers and driving process improvements.

Lead front-end architecture and development for Salesforce Commerce Cloud using SFRA. Architect reusable components, customize ISML templates, optimize performance, ensure responsive and accessible UI, mentor engineers, enforce code quality, and collaborate cross-functionally to deliver scalable eCommerce solutions.

Lead Technical Architect drives end-to-end software development, ensures reusable stable code, mentors engineers, integrates cloud and modern architectures, leads design, reviews, testing, and delivery.

Lead QA activities including creating and executing test cases, automation and API testing, logging and tracking defects, performance and stability testing, coordinating with product and development teams, and maintaining QA documentation and test frameworks.

Lead requirements gathering and analysis for SAP BTP and SAP ERP solutions, coordinate with stakeholders, designers, and developers, manage UAT, workshops, and Agile ceremonies, and ensure system integrations and custom enterprise applications meet business needs.

Lead design and build of generative AI, multimodal, and agentic systems. Develop and fine-tune transformer models, retrieval/knowledge-graph augmented systems, and production APIs. Deploy and monitor ML services in cloud, collaborate cross-functionally, mentor engineers, and ensure safety, evaluation, and scalable MLOps practices.