Sr. Director, AI Enterprise Platform Engineering

Details

At SentinelOne, we are driven by a clear purpose: to give the advantage to those who secure our future. As AI reshapes how organizations build, operate, and innovate, the responsibility to protect them becomes more critical than ever. When you join SentinelOne, your work helps protect global enterprises, critical infrastructure, and the technologies shaping tomorrow.

SentinelOne is at the intersection of AI and security, building an AI-native platform that unifies protection across endpoint, cloud, identity, data, and AI systems. Our platform delivers autonomous detection and response using real-time analytics, intelligent automation, and a unified data foundation.

This Sr. Director role will build the AI foundation that every internal AI use case runs on top of. The platform you create will be the control plane through which all AI activity at SentinelOne is governed, observed, secured, and scaled — serving both custom-developed AI applications built by SentinelOne engineering teams and vendor-deployed AI solutions such as Claude Enterprise and Gemini Enterprise.

Responsibilities

• Own and execute the roadmap for SentinelOne's enterprise AI platform — the Gateway, Harness, and Semantic Layers — moving from direct-to-LLM connections to a governed, multi-model control plane.
• Design and build the AI Gateway layer: centralized identity and AuthN/Z, token budgeting, DLP and content guardrails, multi-model routing and failover, MCP allow-listing, and a full audit trail across every AI request.
• Build and operate the Harness layer: agent orchestration (LangGraph or equivalent), prompt construction and context management, memory and state across multi-turn interactions, model abstraction across Anthropic, OpenAI, Google, and others via providers such as AWS Bedrock and Vertex, and MCP/tool wiring for internal and SaaS-embedded agents.
• Own the technical roadmap for SentinelOne's Claude & Gemini Enterprise plugin framework — a growing library of role-based skills and agents, including secure authoring, testing, and deployment of plugins.
• Partner with Enterprise Data, Enterprise Apps, Product Development, and Infosec to connect the platform to governed data sources and align on security and architectural contracts.
• Govern agent interactions (user-instantiated, internally engineered, SaaS-embedded, or partner-supplied) so every caller passes through the same policy controls.
• Hire, mentor, and technically lead a team of engineers; set standards, review architecture decisions, and create an environment for high technical performance.
• Communicate platform status, architecture decisions, and risk posture clearly to executive stakeholders.

Requirements

• Experience building at least one production platform (AI or otherwise) that enforced centralized policy across multiple consumers: auth/AuthN/Z, rate limiting, observability, and audit logging. Bonus for experience with LLM gateways, model routing, or orchestration.
• Hands-on depth in agent orchestration (LangGraph or equivalent) and routing to hosted model providers such as AWS Bedrock and Google Vertex. Practical understanding of context windows, memory, and tool-calling.
• Demonstrated experience designing and implementing an AI gateway: centralized auth, rate limiting, DLP, observability, and audit logging across multiple model providers. Experience with Kong AI Gateway is a plus.
• Experience building or owning a model evaluation framework that uses eval results to drive model selection, prompt tuning, and routing decisions.
• Familiarity with the Model Context Protocol (MCP) and practical experience governing tool access for agents operating across enterprise systems.
• Hands-on familiarity with enterprise AI deployments, specifically Claude Enterprise (Anthropic) and Gemini Enterprise, including administration, access/policy controls, and integration into governed AI architectures.
• Strong software engineering background; ability to write and review production code. Current stack includes Python 3.11+ with FastAPI, React 18+ with TypeScript, and pydantic.ai for LLM-powered components.
• Demonstrated ability to collaborate across organizational boundaries and build shared architectural contracts.
• Experience evaluating build vs buy vs assemble options, vendor assessment, and total cost of ownership modeling.
• 7+ years of software engineering experience, with at least 3 years in an engineering leadership role and at least 1 year leading a team building AI or ML infrastructure in a production enterprise environment.

Benefits

• Restricted Stock Units (RSUs) and Employee Stock Purchase Plan (ESPP)
• Flexible time off, paid company holidays, paid sick time, gender-neutral parental leave, and grandparent leave
• Medical, dental, and vision coverage; 401(k) with company match; life and disability insurance; health and dependent care FSA
• Voluntary benefits (hospital, accident, critical illness), Employee Assistance Program (EAP), ARAG pre-paid legal, and pet insurance
• Global business travel medical insurance, wellness coach, gym reimbursement, fertility coverage, adoption & surrogacy reimbursement
• Home office allowance and mobile phone reimbursement

Compensation & Legal

• This U.S. role has a base pay range that varies by candidate location. Base Salary Range: $198,750—$298,000 USD.
• SentinelOne participates in the E-Verify Program for all U.S. based roles.