
AI Governance Analyst 1
Datadog · New York, NY
- On site
- Full-time
- $130,000 / year
- New York, NY
Job highlights
- Focus on AI orchestration governance and policy.
- Design and implement AI governance controls.
- Partner with engineering and legal teams.
- Audit AI landscape, code, and data flows.
- Ensure AI systems comply with regulations.
About the role
The Opportunity
Datadog is hiring a Governance Analyst to focus on the unique challenges of AI Orchestration. This role requires a blend of technical acumen, policy understanding, and process design skills to ensure AI systems operate within lawful and policy-compliant boundaries by design. This person will be instrumental in moving the governance model from process review to continuous, embedded constraint.
About The Team
The small, high-impact Applied Privacy & Governance team connects engineering, legal, and product development teams to scale governance, embed security, privacy, and AI safety, and ensure compliance. The rise of AI agents is shifting the team into an "orchestration era," making governance a foundational architecture, not just a gate review.
What You'll Do
AI Orchestration Governance & Process Design
- Develop governance standards and policy enforcement for AI-powered features and internal orchestration systems.
- Design and implement workflows for defining, reviewing, and tracking governance constraints at the prompt, pipeline, and infrastructure level.
- Define and implement audit surfaces for AI-generated code and model behavior to ensure accountability.
- Develop monitoring and reporting frameworks for data flows through automated pipelines and LLM tool-use chains.
- Own the governance lifecycle for new AI features, from risk scoping to operational monitoring.
Cross-Functional Partnership & Influence
- Lead sessions with engineering, product, legal, and compliance to assess risk and design scalable solutions.
- Act as a consultant, translating complex legal/policy requirements into concrete process steps and architectural needs.
- Clearly communicate complex AI and governance risk to audiences ranging from engineers to executives.
- Socialize AI governance best practices, building a culture where compliance is an architectural feature.
Policy & Systems Integration
- Work with Security and Privacy Engineers to ensure policy-as-code systems reflect governance requirements.
- Contribute to the design of data lifecycle management (deletion, retention, access) processes for AI-driven data.
- Develop and maintain key governance documentation, including tailored AI governance policies and risk assessment templates.
What We're Looking For
Must-Haves
- 3+ years experience in a compliance, governance, program management, or technical analyst role in a high-scale tech environment.
- Demonstrated ability to translate complex regulations (GDPR, CCPA, etc.) into implementable process controls and system requirements.
- Experience designing and operationalizing governance, compliance, or risk management workflows for technical teams.
- Strong cross-functional communication and stakeholder management skills.
- Comfort operating with ambiguity and driving initiatives without formal authority.
- Technical literacy: Ability to understand distributed systems (Kafka, Cassandra, Redis) and modern software development/CI/CD pipelines to design integrated controls.
Strong Differentiators
- Direct experience implementing governance controls for AI/ML pipelines or LLM-based product features.
- Familiarity with orchestration frameworks, AI agent architectures, or tool-use systems (e.g., LangChain).
- Experience with Policy-as-Code systems or defining requirements for automated compliance scanning.
- Prior exposure to SDLC governance integration, threat modeling, or privacy impact assessments in a technical capacity.
- Basic coding/scripting skills (e.g., Python, Go) sufficient to understand code and data flows.
Key skills/competency
- AI Governance
- Policy Translation
- Process Design
- Risk Auditing
- Stakeholder Management
- Regulatory Compliance
- AI Orchestration
- LLM
- System Architecture
- Datadog
Skills & topics
- AI Governance
- Governance Analyst
- Compliance
- Risk Management
- AI
- Machine Learning
- LLM
- Policy
- Datadog
- Tech
- SaaS
- Governance
- Analyst
- AI Orchestration
- Policy-as-Code
- GDPR
- CCPA
How to get hired
- Tailor your resume: Highlight experience in compliance, governance, risk management, and AI/ML, using keywords from the job description.
- Showcase technical literacy: Emphasize understanding of distributed systems, CI/CD pipelines, and any scripting/coding skills.
- Demonstrate policy expertise: Provide examples of translating regulations like GDPR/CCPA into actionable controls.
- Prepare for behavioral questions: Be ready to discuss managing ambiguity and influencing cross-functional teams without formal authority.
- Research Datadog: Understand their mission, products, and culture to align your application and interview responses.
Technical preparation
Behavioral questions
Frequently asked questions
- What specific AI governance challenges will the AI Governance Analyst at Datadog focus on?
- The AI Governance Analyst at Datadog will focus on the unique challenges of AI orchestration, ensuring AI systems operate within lawful and policy-compliant boundaries by design. This involves moving governance from process review to continuous, embedded constraints within AI orchestration prompts, system architecture, and LLM pipeline design.
- What is the role of the Applied Privacy & Governance team at Datadog?
- The Applied Privacy & Governance team connects engineering, legal, and product development teams to scale governance, embed security, privacy, and AI safety, and ensure compliance. They are entering an 'orchestration era' where governance is a foundational architecture.
- What technical literacy is expected for the AI Governance Analyst role at Datadog?
- The role requires technical literacy to understand distributed systems (like Kafka, Cassandra, Redis) and modern software development/CI/CD pipelines to design integrated controls. Basic coding/scripting skills in languages like Python or Go are also beneficial for understanding code and data flows.
- How does Datadog approach AI governance in its product development?
- Datadog is integrating governance as an architectural feature, focusing on 'Governance-as-Architecture,' 'Model Output Monitoring,' 'Constraint Layer Auditing,' and 'Policy Implementation Workflow.' They aim to embed controls upstream in prompts, system architecture, and LLM pipeline design.
- What kind of experience is considered a 'strong differentiator' for this AI Governance Analyst position?
- Strong differentiators include direct experience with AI/ML pipeline governance, LLM-based product features, familiarity with orchestration frameworks (e.g., LangChain), Policy-as-Code systems, SDLC governance integration, threat modeling, or privacy impact assessments.
- How will the AI Governance Analyst collaborate with other teams at Datadog?
- The analyst will lead sessions with engineering, product, legal, and compliance teams to assess risk and design solutions. They will also work with Security and Privacy Engineers to integrate policy-as-code systems and contribute to data lifecycle management processes.
- What is Datadog's stance on remote work for the AI Governance Analyst role?
- The job description does not explicitly state the work arrangement. However, given Datadog's global presence and the nature of tech roles, it could be remote, hybrid, or on-site. Candidates should confirm this during the application or interview process.
- What are the compensation and benefits for the AI Governance Analyst at Datadog?
- The estimated yearly salary range is $102,000—$130,000 USD. Datadog also offers new hire stock equity, ESPP, continuous professional development, a strong benefits package including healthcare, dental, parental planning, mental health support, a 401(k) plan, and paid time off.