Key skills
PythonLLM orchestrationAPI integrationcloud platformsdata science fundamentalscontinuous improvementresearchinnovationethicscompliancecollaborationAIMLNLPLLMOpenAILangChainMLOpsAnalyticsFastAPIAWSAzureGCPOpenTelemetryRESTfulCollaboration
About this role
Dentsu is a global marketing and advertising agency, and they are seeking a Senior AI Engineer to design, build, and deploy AI capabilities that enhance their products. The role involves collaborating with various teams to develop scalable AI systems for content personalization and audience analytics, while also championing responsible AI practices.
Responsibilities:
- AI Solution Development: Architect, develop, and maintain AI systems for media products
- Collaboration : Partner with product, engineering, and data teams to translate business needs into technical solutions
- Deployment & Scaling : Implement AI models in production environments, ensuring reliability, scalability, and performance across global markets
- Continuous Improvement : Monitor, evaluate, and iterate on AI models using real-world data and feedback
- Research & Innovation : Stay current with AI/ML advancements; prototype and recommend new technologies to keep our products at the forefront of innovation
- Ethics & Compliance : Champion responsible AI practices, ensuring fairness, transparency, and compliance with data privacy regulations
Requirements:
- Master's degree in Computer Science, Engineering, or related field (PhD a plus)
- Strong Python skills, with experience in LLM orchestration libraries (e.g., LangChain, LlamaIndex, Semantic Kernel), chain-of-thought, and structured reasoning approaches
- Demonstrated experience with enterprise LLMs – their APIs, performance challenges, and how to mitigate those (OpenAI, Anthropic, Cohere, etc.)
- Demonstrated production experience with API conventions and integration into pipelines, e.g. RESTful API, FastAPI, or similar
- Demonstrated experience integrating multiple approaches for extracting highest-quality output from LLMs, e.g. prompt engineering, multi-agents, structured output validation, hybrid RAG, in-context learning (ICL), or NLP- or ontology-powered layering
- Proficiency with document processing pipelines (text extraction, chunking, embedding)
- Demonstrated production experience with measuring and improving AI systems, tracing and AI observability (e.g. Arize, OpenTelemetry, LangSmith)
- Strong foundation in data science fundamentals, including data analysis, statistical methods, and experience working with structured and unstructured data
- Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools