We are seeking a Sr. Director, Infrastructure, SRE, & Security to lead our Infrastructure, SRE & Security team in building the cloud and data infrastructure that enables our AI platform.
\nAs a key member of our Engineering department, you will be responsible for owning the architecture, reliability, and cost efficiency of our cloud infrastructure, driving full IaC coverage and leading Kubernetes operations at scale.
\nYou will also own data infrastructure operations, cost governance, and security hardening, partnering with Data Product Engineering on modernizing data delivery infrastructure.
\nIn addition, you will lead security posture management across cloud, application, and identity layers, defining and instrumenting cost-per-unit metrics, implementing per-team budgets with automated alerting, and giving leadership direct visibility into infrastructure efficiency.
\nYou will operate internal developer platforms with self-service onboarding, CI/CD, and observability infrastructure that improves engineering velocity.
\nYou will also own incident response, on-call rotations, and post-mortem processes, driving reduction in preventable operational incidents and maintaining high availability SLAs.
\nLastly, you will lead, recruit, and grow a globally distributed team of cloud, data, and security engineers, fostering a culture of ownership and technical excellence.
\nWhat you bring to Komodo Health:
\nAI Use Expectations:
\nAdditional skills and experience we’d prioritize (nice to have):
\nThe pay range for this role is $225,000-$270,000 USD per year, depending on location. This position may be eligible for performance-based bonuses and equity awards.
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\nAs employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
\nThis role is part of Microsoft AI’s Superintelligence Team. The MAIST is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence , ultra-capable systems that remain controllable, safety-aligned, and anchored to human values.
\nOur mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control. We aim to deliver breakthroughs that benefit society , advancing science, education, and global well-being.
\nWe are hiring a Product Manager to own AI model security , the discipline of making our frontier models resilient against adversarial attack and purpose-built for security practitioners.
\nThis role has a dual mandate: (1) harden our models against the full spectrum of LLM security threats , prompt injection, data exfiltration, jailbreaking, training data extraction, zero-day exploit generation, model poisoning, and agentic workflow exploitation , and (2) partner closely with Microsoft Security product teams (Azure Security, Security Copilot) to ensure our models deliver best-in-class capabilities for real-world security workflows.
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\nDrive zero-day and exploit defense: Work with researchers to evaluate and mitigate the risk of models being used to generate zero-day exploits, malware, or novel attack vectors.
\nBuild and scale red-teaming frameworks: Design, run, and iterate adversarial testing programs , both automated and human-driven , to continuously probe model vulnerabilities.
\nEstablish metrics (e.g., jailbreak success rate, injection bypass rate, exfiltration resistance) and drive measurable improvement over time.
\nPartner with Microsoft Security product teams: Work closely with Azure Security and Security Copilot teams to translate their product requirements into model training priorities.
\nEnsure our models are purpose-built for threat detection, incident triage, vulnerability assessment, log analysis, and compliance reasoning.
\nDefine security-specific model evaluations: Build benchmark suites and evaluation frameworks that measure real-world security usefulness , not just academic performance.
\nDrive training data strategy to improve domain-specific model quality for security practitioners.
\nShape security policy and launch readiness: Establish clear security criteria for model launches.
\nOwn the security dimension of go/no-go decisions, with frameworks that balance capability, risk, and deployment context.
\nStay at the frontier: Track the rapidly evolving LLM security landscape , new attack techniques, emerging standards (OWASP, NIST AI RMF), regulatory requirements (EU AI Act), and academic research.
\nTranslate what you learn into actionable product priorities.
\nInfluence model training and architecture: Partner with researchers and engineers to embed security considerations into model training, fine-tuning, RLHF, and post-training safeguards.
\nQualifications:
\nBachelor’s Degree AND 5+ years experience in product management, security engineering, or software development OR equivalent experience
\nDemonstrated hands-on experience with AI/ML systems , you have personally built, evaluated, or shipped ML-powered products or security tools
\nDeep familiarity with LLM security threats: prompt injection, jailbreaking, data exfiltration, adversarial attacks on generative models , through professional experience, red-teaming, or security research
\nExperience defining product requirements and driving decisions in partnership with researchers or ML engineers
\nTrack record of building evaluation systems, security benchmarks, or adversarial testing frameworks , not just consuming them
\nAbility to operate autonomously, make decisions with incomplete information, and drive projects from ambiguity to shipped outcomes
\nPreferred Qualifications:
\nTechnical background in computer science, security, or AI/ML , a postgraduate degree is a plus but not required
\nExperience in offensive security, penetration testing, or red teaming , ideally applied to AI/ML systems
\nFamiliarity with security workflows and tooling (SIEM, SOAR, EDR, threat intelligence platforms) and how practitioners use them in production
\nUnderstanding of the model lifecycle (pre-training, fine-tuning, RLHF, deployment, monitoring) and where security interventions are most effective
\nExperience working with or within enterprise security organizations (e.g., Microsoft Security, CrowdStrike, Palo Alto Networks, or similar)
\nPublished research, blog posts, or public contributions in AI security, adversarial ML, or LLM red teaming
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\nIn this role, you will design and implement AI-powered security tools, proactively address vulnerabilities, and champion secure engineering practices across the organisation.
\nIdeal candidates are passionate about impactful innovation, excel at writing clean, efficient code, and thrive in fast-paced environments to support xAI's mission of creating a trusted and secure global digital platform.
\nResponsibilities:
\nBasic Qualifications:
\nPreferred Skills and Experience:
\nITAR Requirements:
\nTo conform to U.S. Government export regulations, applicant must be a (i) U.S. citizen or national, (ii) U.S. lawful, permanent resident (aka green card holder), (iii) Refugee under 8 U.S.C. § 1157, or (iv) Asylee under 8 U.S.C. § 1158, or be eligible to obtain the required authorisations from the U.S. Department of State. Learn more about the ITAR here.
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\nYou'll conduct hands-on penetration testing, lead red team engagements, and collaborate with blue team counterparts to validate and improve detection and response capabilities. Your work will directly influence how Stripe builds, ships, and secures financial infrastructure used by millions of businesses worldwide.
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\nContribute to internal security tooling repositories and champion engineering best practices within the team.
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\nProduce clear, actionable reports that communicate technical findings, business risk, and remediation guidance to both technical and non-technical stakeholders.
\nAct as a subject-matter expert and primary point of contact for stakeholder teams engaged in offensive security programs and Stripe-wide security initiatives.
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\nThis role combines technical depth, strategic thinking, and the autonomy to design workflows that will protect infrastructure driving the future of AI.
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\nPreferred Qualifications:
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\nThe range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location.
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