Manager I, Engineering - Applied AI - Natural Language & Conversational Interfaces
Lead engineering teams building natural language interfaces and conversational AI systems using LLMs, RAG, and agentic architectures. Requires technical expertise in AI/ML/NLP, people management, and experience shipping LLM-powered products.
About the job
What You’ll Do
- Lead and develop a team of engineers and applied scientists building NLQ translation systems, conversational agents, or AI-powered interfaces
- Own the delivery of high-quality natural language capabilities, from semantic understanding and contextual retrieval to query generation and agentic reasoning
- Build products that create data flywheels: design systems that capture user intent and feedback to continuously improve model quality and train differentiating capabilities
- Drive evaluation and iteration practices for AI systems, including building offline and online evaluation pipelines to measure quality and detect drift
- Partner with product managers and cross-functional teams to expand AI capabilities across the Datadog platform
- Navigate the unique challenges of shipping LLM-powered products: balancing accuracy, latency, cost, and safety considerations
- Support career growth for engineers through coaching, feedback, and fostering a culture of experimentation, innovation, and learning
- Drive day-to-day execution and promote high standards for operational excellence, system reliability, and technical quality
- Participate in hiring and help shape the future team as the organization grows
- Contribute to cross-team collaboration and knowledge sharing across the broader AI organization
Who You Are
- A technical leader with experience in AI, machine learning, or NLP systems
- Proven experience building and shipping LLM-powered products, conversational AI, or natural language interfaces
- A product builder who thinks beyond features, designing systems that generate data, learn from usage, and compound in value over time
- Experience leading and mentoring engineers; ready to grow into broader leadership responsibilities
- Strong technical expertise in one or more areas: large language models, retrieval-augmented generation (RAG), semantic search, agentic systems, deep learning, or NLP
- Comfortable working with Product to break down ambiguous problems, foster an experimental culture and iterate quickly on AI systems where quality is probabilistic
- Familiarity with evaluation methodologies for AI systems, both offline benchmarks and online metrics
- A people-focused manager able to develop and support strong engineering talent in a fast-moving domain
- BS/MS/PhD in Machine Learning, Computer Science, Engineering, or related field, or equivalent professional experience
Skills
LLMs, Retrieval-Augmented Generation, RAG, Natural Language Processing, NLP, Conversational AI, Semantic Search, Agentic Systems, Deep Learning, Machine Learning, Evaluation Frameworks, Llm Query Translation
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