Manager I, Engineering - Applied AI - Natural Language & Conversational Interfaces
Datadog · New York City, NY · Leadership
About this role
Datadog is hiring a manager-level Engineering Manager in the software engineering function based in New York City, NY. The posting calls out experience with Spring, LLMs, RAG, NLP. Compensation is listed at $187,000–$240,000 per year.
- Role
- Engineering Manager
- Function
- software engineering
- Level
- manager
- Track
- hybrid
- Employment
- Full-time
- Location
- New York City, NY
- Department
- Leadership
More roles at Datadog
Job description
from Datadog careersDatadog's Applied AI group is building the AI capabilities that transform how users interact with our platform. Our Natural Language Query (NLQ) and Command-I (Cmd-I) teams are at the forefront of this transformation, enabling users to query telemetry data, investigate production issues, and configure Datadog through natural language and intelligent conversational agents.
As an Engineering Manager I in Applied AI, you will lead a team of engineers and applied scientists building natural language interfaces and conversational AI systems. Your teams will work on challenges spanning LLM-powered query translation, context-aware retrieval systems, agentic architectures, and evaluation frameworks. You will guide technical execution, support team growth, and collaborate across engineering, product, and research to deliver AI experiences that fundamentally change how customers use Datadog.
At Datadog, we place value in our office culture, the relationships and collaboration it builds and the creativity it brings. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.
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