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Principal AI Developer, Experience Architect
SentinelOnePrincipal AI Developer Experience Architect at SentinelOne, designing AI integration into engineering workflows for an AI-native cybersecurity platform, emphasizing standards and developer experience.
About the role
Key responsibilities & impact- Architect the AI Engineering Layer
- Define the end‑to‑end architecture for AI-augmented development at SentinelOne, centered on enterprise-grade AI coding assistants and LLM platforms integrated with our IDEs, CI/CD pipelines, and internal platforms.
- Design how large-context LLMs consume our codebase and documentation context so that AI assistance scales safely across hundreds of repos.
- Establish reusable patterns for agentic workflows with clear rollback and validation strategies.
- Own AI Guardrails, Skills, and Standards
- Define and maintain SentinelOne AI Coding Standards and a global skills & requirements framework that all AI coding tools (our chosen AI coding assistants, PR bots, agents) must enforce, including language, framework, security, performance, and reliability patterns.
- Translate these standards into prompt templates, tool configurations, and policy‑as‑code so they are enforced automatically rather than via documentation alone.
- Partner with InfoSec, Data Governance, and Legal to ensure all AI tooling adheres to SentinelOne’s AI Policies, data residency, and FedRAMP compliance requirements.
- Implement AI-Driven Code Review and Safety as Code
- Lead the integration of AI-powered code review tools that use AST analysis and static/dynamic checks to enforce style, security, performance, and reliability standards before human review.
- Integrate AI review signals with our SRE observability stack (logs, metrics, traces) to correlate code changes with incidents and anomalies, closing the loop from PR to production behavior.
- Encode “safety as code” by integrating test coverage, performance scans, and progressive delivery patterns (canaries, blue/green) into AI‑authored change flows.
- Lead Vendor Evaluation and Integration
- Serve as the principal technical owner for AI developer tooling evaluations using structured evaluation criteria and data-driven analysis.
- Work closely with the DevEx leadership and TPM to design and run POCs, define technical success criteria, and produce executive‑ready recommendations.
- Ensure all vendors meet SentinelOne’s security, privacy, and data governance standards.
- Drive Developer Adoption and Experience
- Act as the technical face of AI DevEx to engineering: publish guidance, patterns, and internal frameworks that make AI tooling a seamless part of everyday work rather than a side experiment.
- Partner with the AI Champions Network and Learning & Development to define curricula, hands-on labs, and “day‑in‑the‑life” workflows that level up prompt engineering and AI‑assisted development skills across developer organizations.
- Collaborate across the SentinelOne developer community to translate adoption and productivity signals into DORA metrics and ROI narratives that are credible to Engineering Leadership, Finance, and the CFO.
- Partner on Reliability, Metrics, and Governance
- Work with SRE and Reliability Engineering to ensure AI‑accelerated delivery improves MTTR, CFR, and SLO performance.
- Participate in the DevEx governance model to prioritize initiatives, manage risk, and align AI DevEx roadmaps with company objectives.
- Own the engineering intelligence dashboards and leadership reports to surface the impact of AI tooling on developer productivity metrics.
Requirements
What you’ll need- 10+ years in software engineering, platform/dev tools, or infrastructure engineering, including significant experience operating at Staff/Principal level in a 300+ engineer product organization.
- 3+ years designing and shipping LLM‑powered developer tools or workflows in production environments.
- Proven track record of architecting developer platforms or large‑scale internal tooling used by hundreds of engineers.
- Deep understanding of LLM context window design, retrieval strategies, prompt engineering at scale, and how they interact with large polyglot codebases.
- Hands-on experience integrating at least one enterprise AI coding assistant into IDEs and Git hosting platforms.
- Strong background in AST-based code analysis, static/dynamic analysis, and policy-as-code for automated PR review.
- Solid understanding of CI/CD systems and progressive delivery and how to embed AI in those pipelines.
- Strong grounding in security and compliance for SaaS and AI/ML systems.
- Experience acting as a cross‑org technical leader: aligning Staff/Principal engineers, EMs, and PMs around a shared architecture and standard.
- Comfortable presenting technical tradeoffs and ROI to senior leadership, and defending architecture choices with data.
- Proven ability to mentor and partner with the entire Product and Technology organization to deliver complex multi‑quarter programs.
- Excellent written and verbal communication skills; able to produce clear design docs, evaluation criteria, and developer‑facing guidance that drive alignment at scale.
Benefits
Comp & perks- Medical, Vision, Dental, 401(k), Commuter, Health and Dependent FSA
- Unlimited PTO
- Industry-leading gender-neutral parental leave
- Paid company holidays
- Paid sick time
- Employee stock purchase program
- Disability and life insurance
- Employee assistance program
- Gym membership reimbursement
- Cell phone reimbursement
- Numerous company-sponsored events, including regular happy hours and team-building events
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
AI architectureLLM designprompt engineeringAST analysisstatic analysisdynamic analysispolicy-as-codeCI/CD systemsprogressive deliverysecurity compliance
Soft Skills
technical leadershipmentoringcommunicationcollaborationguidance publishingrisk managementalignmentpresentation skillsevaluation criteria developmentcross-organizational partnership