Senior Manager, Engineering

About this role

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Skills you'll use

What you'll do

• Lead the architecture, design, and productionization of scalable microservices and AI-enabled product capabilities from concept through production deployment.
• Lead AI platform system design and implementation, ensuring robust, secure, maintainable, and well-governed solutions across Java/Spring Boot and Python/FastAPI services where appropriate.
• Drive the architecture and delivery of Generative AI and Agentic AI solutions, including MCP-based architectures, agent orchestration, tool integration, intent classification, agent state management, and multi-agent workflows.
• Establish engineering patterns for integrating LLM APIs, including OpenAI, Azure OpenAI, Anthropic, and equivalent providers, with attention to security, reliability, cost, rate limits, and token efficiency.
• Guide teams in productionizing GenAI use cases such as AI chatbots, summarization, classification, intelligent search, Q&A, and embedding-based retrieval.
• Lead the design of systems that query and manage large-scale structured and unstructured data, including SQL, NoSQL, MongoDB, SingleStore, and Postgres, with appropriate data modeling and performance practices.
• Establish architectural approaches for agentic AI systems, embeddings, vector search, context management, caching, latency optimization, and observability for AI enabled applications.
• Leverage GitHub Copilot and AI-assisted development tools to accelerate software delivery, improve code quality, and enhance engineering productivity.
• Take ownership of development, maintenance, testing strategy, design discussions, and operations of the team, including containerized API services.
• Participate in all aspects of agile software development, including design, implementation, deployment, sprint planning, and continuous improvement.

Who can apply

• Take ownership of development, maintenance, testing strategy, design discussions, and operations of the team, including containerized API services.
• Participate in all aspects of agile software development, including design, implementation, deployment, sprint planning, and continuous improvement.
• Own the end-to-end lifecycle of new product features and components, partnering with product, design, data, and AI engineering stakeholders.
• Ensure application performance, uptime, scale, and reliability while maintaining high standards of code quality, security, and thoughtful application design.
• Work with a cross-functional team on products and features to drive growth and meaningful customer outcomes.
• Develop engineering talent through coaching, technical mentorship, constructive reviews, and clear accountability for delivery outcomes.
• Research, evaluate, and recommend emerging technologies, frameworks, and engineering practices that can strengthen the product and platform.
• Influence product development through important technical decisions, system architecture, development practices, and long-term technology strategy.

About NielsenIQ

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