Datadog
Enterprise · Observability
- HQ
- New York, US
- Founded
- 2010
- Size
- 7,000+
- Funding
- Public (DDOG)
- Website
- datadoghq.com
- Blog
- datadoghq.com
Products
Currently tracking 35 active AI roles, with 87 new openings in the last 4 weeks. Primary focus: Agent · Engineering. Salary range $155k–$385k (avg $242k).
Enterprise · Observability
Datadog has 43 active AI-related job listings. The majority of these roles, 58%, are focused on agents. Engineering is the dominant function, with a significant number of roles also in Product and Research. The company is actively hiring in the United States and France. Frequent tech tags include agent orchestration, evals, and model serving, suggesting a focus on building and deploying AI agents.
Datadog currently has 43 active AI-related roles in our index. The most common open titles are: AI Research Engineer - Datadog AI Research (DAIR) (2), Senior Software Engineer (AI) (2), AI Research Scientist - Datadog AI Research (DAIR), AI Research Scientist – Datadog AI Research (DAIR), Director, Product Management - AI Observability. Most positions are in Engineering and Product.
Datadog's active AI hiring is concentrated in: agents (51%), application (16%), evaluation (9%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Datadog is hiring AI talent in: United States (29 roles), France (13 roles), Spain (9 roles), Portugal (8 roles).
Job postings at Datadog most frequently reference: agent orchestration, evals, llm observability, model serving, inference infra.
In the past 30 days, Datadog has posted 9 new AI-related roles. That is a +80% change versus the prior 30 days (5 → 9).
| Title | Stage | AI score |
|---|---|---|
| Senior LLM Engineer Senior LLM Engineer to build AI-assisted tools for Datadog developers, focusing on LLM-based agents, generating tests, fixing bugs, and improving performance. The role involves working with users, designers, and PMs to prototype, iterate, and ship these systems, integrating them with Datadog products and following the latest research in LLM prompting and agents. | Agent | 8 |
| Senior AI Engineer - Bits AI Security Analyst Datadog is seeking a Senior AI Engineer to build the next generation of AI-driven security capabilities, focusing on their AI agent that leverages LLMs for security analysis and threat investigation. The role involves developing tools, retrieval and planning strategies, guardrails, prompt management, and shipping AI-driven security features. | Agent |
| 8 |
| Senior Software Engineer (Agent Engineer) - AI Code Gen Datadog is seeking a Senior Software Engineer to build AI-assisted tools for developers, focusing on LLM-based agents for tasks like test generation and bug fixing. The role involves working on prompts, evals, agent tools, productionizing systems, and integrating them with Datadog products. | Agent | 8 |
| Senior Generative AI Engineer Senior Generative AI Engineer to build AI-assisted tools for Datadog developers, focusing on LLM-based agents for tasks like test generation and bug fixing. The role involves prompt engineering, agent tool development, productionization, and integration with existing Datadog products. | Agent | 7 |
| Senior AI Engineer Senior AI Engineer to build AI-assisted tools for Datadog developers, focusing on LLM-based agents for tasks like test generation and bug fixing. The role involves working closely with users, prototyping, productionizing systems, and integrating them with Datadog products. | Agent | 7 |
| Senior Software Engineer (AI) Senior Software Engineer to build AI-focused developer workflows and tools, including AI agents, prompts, and evals, for Datadog customers. The role involves ideation, prototyping, shipping features, and supporting other teams in productionizing AI workflows. | Agent | 7 |
| Senior Applied Scientist This role focuses on building and deploying ML-powered features within Datadog's observability platform, specifically in areas like anomaly detection and error outlier analysis. The scientist will design, research, build, and scale these features, working closely with engineering and product teams, and will be involved in the full lifecycle from exploration to production monitoring. | Agent | 7 |