• Translate product needs into agentic tools and services and ship them to production. • Scale prototypes to large numbers of users. • Improve and test our semantic search service. • Build evaluation pipelines for code retrieval and coding task performance.

Role Description We are hiring a Senior Data Scientist / AI Engineer to design, build and scale production-grade AI solutions, with a strong focus on Generative AI, NLP, and healthcare-related use cases. This role is suited for a hands-on technical leader who can translate complex business and domain problems into reliable AI systems that create value, work closely with cross-functional teams, and mentor high-performing data science talent across multiple geographies. The ideal candidate brings strong machine learning fundamentals, deep experience with NLP and transformer-based models, practical exposure to LLMs and RAG systems, and the ability to deliver measurable business and operational impact in real-world environments. Key Responsibilities - Design, build, and deploy end-to-end AI and machine learning solutions, with a focus on GenAI, NLP, and healthcare applications. - Develop and productionize LLM-based workflows, including prompt engineering, evaluation frameworks, fine-tuning approaches, and Retrieval-Augmented Generation systems. - Translate ambiguous business and healthcare problems into structured data science solutions with clear success metrics. - Own the full model lifecycle, including data preparation, experimentation, validation, documentation and articulation of results, deployment, monitoring, and continuous improvement following RAI guidelines. - Work with large-scale structured and unstructured data, including clinical, operational, claims, member, provider, or other healthcare-related datasets. - Partner with product, engineering, business, clinical, and compliance stakeholders to ensure solutions are scalable, explainable, secure, and aligned with business needs. - Lead, mentor, and develop a team of data scientists, and AI engineers, setting high standards for technical quality, analytical rigor, and delivery discipline. - Drive best practices in model development, code quality, documentation, reproducibility, and responsible AI. Qualifications - 8+ years of experience in developing and implementing end-to-end solutions using Machine Learning and AI tools. - 5+ years of hands-on experience in NLP, deep learning, and transformer-based models. - 2+ years of practical experience building end-to-end Generative AI solutions, including LLM workflows, fine-tuning, evaluation, and RAG-based systems. - Strong proficiency in Python and PySpark is mandatory. - Proven experience building and deploying production-grade ML or AI systems at scale. - Strong business acumen with the ability to convert complex business problems into practical AI solutions that deliver measurable impact. - 2+ years of experience leading, mentoring, or managing high-performing data science teams is highly desirable. - Excellent written and verbal communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders. - Experience working in a matrix organization. Preferred Qualifications - Experience in the healthcare domain is highly desirable, especially in areas such as clinical AI, payer/provider analytics, population health, claims, care management, medical operations, or health data platforms. - Experience working with healthcare data standards, privacy requirements, regulated environments, or responsible AI considerations in healthcare. - Hands-on experience with Azure, Databricks, or equivalent cloud and data platforms. - Working knowledge of MLOps, CI/CD for ML, model monitoring, model governance, and scalable deployment patterns. - Experience optimizing AI systems for accuracy, performance, latency, reliability, cost, and maintainability. - Exposure to multimodal AI, knowledge graphs, medical text analytics, or clinical decision support use cases is a plus. What Good Looks Like - Strong technical depth combined with practical judgment. - Ability to operate in ambiguous environments and bring structure to complex problems. - High ownership mindset with a focus on outcomes, not just models. - Clear communication, strong stakeholder management, and the ability to influence across teams. - Passion for building AI solutions that are robust, responsible, and meaningful in a healthcare context.

Title: Associate Director, AI Engineer locations New York - 150 E 42nd time type Full time job requisition id R1117614 Job Description: Reports To: VP, AI Agents & Automation Team: AI Agents & Automation Role Summary We are seeking an Associate Director, AI Engineer to help build the next generation of AI agents at dentsu. This role is a senior technical individual contributor position focused on designing and delivering multi‑agent systems that transform data intelligence into automated, client‑facing workflows. You will partner closely with the VP of AI Agents & Automation, write production code, set engineering patterns, and collaborate with an offshore engineering team to deliver scalable, reliable AI products. This role blends architectural decision‑making with hands‑on development. Key Responsibilities - Design and build multi‑agent systems using LLM orchestration frameworks for client‑facing AI products. - Implement end‑to‑end AI orchestration use cases for clients, ensuring reliability, maintainability, and high-quality delivery. - Build agentic wrappers and interfaces around data science models (e.g., MMM, forecasting, incrementality) to support conversational access. - Configure Genie spaces to enable client data exploration and self‑service analytics. - Develop reusable agent components, prompt templates, and tool‑use libraries to accelerate future deployments. - Evaluate LLM providers based on capability, cost, and latency, and recommend optimal options for each use case. - Collaborate with the Offshore Director Staff AI Engineer on architecture direction, design patterns, and coding standards. - Write production‑grade Python with appropriate error handling, observability, CI/CD integration, and deployment automation. - Partner closely with Data Scientists to understand models and create resilient, accurate agent interfaces. - Contribute to technical documentation, architecture decision records, and operational runbooks. Required Qualifications - 5+ years of software engineering experience with strong Python skills. - 2+ years of hands‑on experience working with LLMs (e.g., prompt engineering, RAG, function calling, agent frameworks). - Experience with at least one agent orchestration framework (LangChain, LangGraph, AutoGen, CrewAI, or similar). - Strong system design skills, including API architecture and distributed systems. - Experience with cloud platforms (Azure preferred) and container orchestration. - Familiarity with vector databases, embeddings, and large‑scale RAG systems. - Strong debugging, performance optimization, and problem‑solving skills. - Effective collaboration skills for partnering with distributed teams across regions and time zones. Preferred Qualifications - Experience with Databricks and/or Genie. - Background in media, advertising, or marketing technology. - Experience with MLOps, model‑serving infrastructure, and production model lifecycle. - Experience building conversational AI or copilot‑style products. - Open‑source contributions related to agentic AI. The annual salary range for this position is $94,000 - $152,662. Placement within the salary range is based on a variety of factors, including relevant experience, knowledge, skills, and other factors permitted by law. Benefits available with this position include: • Medical, vision, and dental insurance, • Life insurance, • Short-term and long-term disability insurance, • 401k, • Flexible paid time off, • At least 15 paid holidays per year, • Paid sick and safe leave, and • Paid parental leave. Dentsu also complies with applicable state and local laws regarding employee leave benefits, including, but not limited to providing time off pursuant to the Colorado Healthy Families and Workplaces Act, in accordance with its plans and policies. At dentsu, we believe great work happens when we’re connected. Our way of working combines flexibility with in-person collaboration to spark ideas and strengthen our teams. Employees who live within a commutable distance of one of our hub offices, currently located in Chicago, metro Detroit, Los Angeles, and New York City, are required and expected to work from the office three days per week (two days per week for employees based in Los Angeles). Dentsu may designate other Hub offices at any time. Those who live outside a commutable range may be designated as remote, depending on the role and business needs. Regardless of your work location, we expect our employees to be flexible to meet the needs of our Company and clients, which may include attendance in an office. Location: New York - 150 E 42nd Brand: Dentsu Media Time Type: Full time Contract Type: Permanent Dentsu is committed to providing equal employment opportunities to all applicants and employees. We do this without regard to race, color, national origin, sex , sexual orientation, gender identity, age, pregnancy, childbirth or related medical conditions, ancestry, physical or mental disability, marital status, political affiliation, religious practices and observances, citizenship status, genetic information, veteran status, or any other basis protected under applicable federal, state, or local law.

• 参与 AI Agent 产品的全生命周期开发，包括 Web 体验、API 服务、Agent 编排、工具调用、Agent Loop、任务规划、执行反馈、状态管理和结果持久化。 • 设计和实现面向生产环境的 Agent 产品能力，包括 API 服务、任务队列、异步流程、数据模型、权限、计费和业务状态管理等核心模块。 • 构建和优化 Agent 与工具系统之间的调用链路，提升执行稳定性、可观测性、容错能力和扩展能力。 • 参与多 Agent 协作、工具路由、上下文管理、模型选择、任务重试、异常恢复等复杂工程问题的设计与落地。 • 参与 Web 应用开发与维护，完成产品功能、交互流程、前端状态管理和用户体验优化。 • 负责 API 服务、后台任务系统、数据层、Monorepo 工程化及 Docker 部署流程的开发、优化与维护。 • 与产品、设计和工程团队协作，将 AI 能力转化为稳定、可交付、可规模化的产品功能。 • 持续探索 AI 辅助开发和 Agent 工程最佳实践，输出高质量、可维护、可测试的代码。