Jobs at dentsu

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.

The role involves creating solution architectures, exploring options for efficiency, overseeing other architects, and ensuring compliance with standards.

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.

Lead ML Engineer responsible for end-to-end software development: design, implementation, testing, documentation, and releases. Ensures code reusability, stability, security, and performance. Owns delivery of complex features, provides technical guidance, mentors engineers, delivers trainings, integrates new technologies, and produces accurate estimates.

Build and maintain scalable Azure and Databricks ETL/ELT pipelines using SQL and Python/PySpark. Design cloud-native data lakes, ingest/process data with ADF/ADLS, optimize data models, monitor pipeline health, troubleshoot failures, and collaborate with architects, QA, DevOps, and business teams.

Design, build, and operate scalable MLOps frameworks on GCP. Automate deployment, CI/CD, IaC, model serving (Vertex AI Endpoints), monitoring, and lifecycle management for Python ML models. Ensure production reliability, scalability, security, and governance across environments.

Lead GenAI engineer role to design, build, and deploy production-grade LLM-based, multimodal, and agentic systems. Responsibilities include model fine-tuning, retrieval and KG-augmented systems, API/microservice deployment, cloud/MLOps integration, monitoring, mentoring, and cross-functional collaboration to deliver scalable, safe, and cost-optimized AI solutions.

Build and deploy production-grade generative AI and multimodal systems: design agentic workflows, fine-tune transformer models, implement retrieval and KG-augmented systems, create scalable APIs/microservices, and collaborate with engineering, CX, and MLOps teams to ensure monitoring, evaluation, and hallucination control.

Lead design and implement enterprise Adobe Workfront and Fusion solutions. Run discovery workshops, define target-state architecture, drive integrations (APIs, data flows), provide technical leadership, establish governance and best practices, support pre-sales, and align solutions to business KPIs.

Lead technical design, architecture, and delivery of Salesforce Commerce Cloud (SFCC) and OMS solutions. Architect SFRA/SiteGenesis implementations, design integrations with third-party systems, guide development teams, enforce best practices, troubleshoot production issues, support CI/CD and release processes, and mentor developers while ensuring security, performance, and compliance for global ecommerce.

The Tech Lead will oversee integration and automation solutions, create technical specifications, guide the tech team, ensure timely delivery, and support impact analysis on systems.

Lead QA to embed quality across solution delivery: define and maintain unit tests, design telemetry pipelines, manage defects and test environments, mentor engineers, present risks to stakeholders, and lead QA for data migration and performance testing of Azure-hosted, containerized distributed systems.

Design and oversee technical architecture, define system standards, collaborate with stakeholders, guide engineering teams on implementation, ensure scalability, reliability, and alignment with business goals.

The AI Lead Engineer will design scalable AI and GenAI systems, lead complex solution designs, and ensure production-grade implementation of AI solutions without formal management.

Owner of quality for solution delivery: develop and maintain unit and automated tests (Playwright/TypeScript), implement performance testing with k6, build observability/telemetry dashboards (Grafana/Prometheus/InfluxDB), ensure production-like test environments (Kubernetes/Docker/Kafka), integrate tests into Azure DevOps CI/CD, manage defects and release decisions, engage stakeholders with clear reports, and mentor engineers to raise test quality.

Lead project teams to deliver scope, schedule, cost, and quality outcomes. Manage budgets, risks, stakeholders, governance, schedules, dependencies, and resources. Support business cases, track benefits realization, and drive communication, conflict resolution, and project controls.

Lead architecture and delivery of Adobe Experience Platform and Adobe Journey Optimizer solutions: data ingestion, identity resolution, audience segmentation, journey orchestration, activations, governance, and platform operations while mentoring engineers and collaborating with marketing and product stakeholders.

Lead testing and automation efforts: develop and architect test automation scripts and frameworks, perform manual validation as needed, create test strategies and plans, write feature test reports, support UATs, mentor team members, communicate bugs and findings, and liaise with customers. Work with CI/CD, cloud platforms, and automation tools.