Security Guard Jobs

About Prophecy The leader in AI-native data preparation and analysis, Prophecy is revolutionizing how the world’s top enterprises turn data chaos into reliable insights. We introduce the AI-native data lifecycle (generate, refine, deploy) where our industry leading AI agents and humans work hand-in-hand in visual and document interfaces to analyze, transform and prepare data, to ship trusted insights at enterprise scale. Don’t miss the rocket ship—join Prophecy and build the next data revolution. Position Summary This is a high-impact opportunity to be a senior DevOps engineer in a fast-growing startup, based in Prophecy’s India engineering center. You will own and evolve the foundations that keep our engineering org fast, secure, and cost-efficient at scale — spanning cloud cost management, security DevOps, and CI/CD and engineering operations. You will work with a team of dynamic engineers who take pride in solving complex problems, and you will have the autonomy to set direction in your areas of ownership. The Impact You Will Have Cloud cost (FinOps) Own and evolve our cloud cost optimization program across AWS, Azure, GCP, Databricks, Snowflake and Bigquery building on the programmatic monitoring and controls Analyze billing, asset-inventory, and utilization data across departments to identify wasteful spend and provide actionable insights to optimize it. Develop and maintain cost optimization strategies, roadmaps, and forecasting models Partner with engineering teams to design cost-efficient architectures without compromising scalability or reliability. Build and maintain automation for infrastructure provisioning, scaling, and cost control. Security DevOps Partner with engineering and security to drive our security-hardening program across workstreams such as identity & access governance, secrets & credential lifecycle, cloud access, and CI/CD hardening. Implement and automate guardrails: secrets management, least-privilege access, cr

About the Role As a Cloud Platform Engineer at Supabase, you’ll join Cloud Engineering, part of Engineering Operations, and shape the foundations that let engineering teams build, ship, and operate infrastructure safely and independently across AWS and GCP. This is a role spanning cloud governance, platform engineering, and hands-on operations. You’ll work across AWS and GCP account structure, identity and access management, Infrastructure as Code (IaC), reusable platform primitives, security boundaries, and self-service workflows for engineers. You’ll be joining at a point where many of these foundations are being actively defined or reworked. We’re looking for someone who can take ambiguous, messy, business-critical infrastructure problems and turn them into pragmatic systems, tools, standards, and written guidance that scale with the company and empower teams to go faster. What You’ll Be Responsible For Designing and implementing cloud governance across AWS and GCP, including identity, account organization, access controls, and guardrails. Building reusable infrastructure and building blocks using Infrastructure as Code (IaC), enabling teams to provision and manage infrastructure safely and consistently. Creating self-service capabilities that reduce organizational friction and let engineers move more quickly within sensible boundaries. Owning resource governance and visibility: management tagging, a trustworthy inventory of what exists and who owns it, and consistent cross-account billing data. Developing reusable security primitives, including secrets storage, KMS, certificate management, token vending, direct service-to-service authentication, mTLS, and related platform services. Owning cloud-level network and operational primitives: IP address management, DNS, and health signals such as service-limit and quota alerting. Combining software engineering with hands-on operations and total ownership: building, deploying, monitoring, troubleshooting, and improving

Amplitude's Cloud Platform team builds the systems that every Amplitude engineer relies on every day to ship code — and we're rebuilding them for the AI era. As a Staff Platform Engineer, you'll set technical direction for the platform across teams, lead our highest-complexity and highest-leverage initiatives, and shape a platform where AI agents are first-class users alongside humans: kicking off deploys, opening pull requests against infrastructure, and triaging incidents, so a single engineer can get the throughput of a team. You'll operate across team boundaries — partnering with product engineering, fellow Staff+ engineers, and engineering leadership to make Kubernetes and cloud infrastructure effortless across the entire engineering org. You'll build the self-service automation, shared standards, and scalable AWS and GCP infrastructure that let dozens of product teams ship faster, safer, and with less cognitive load — and you'll multiply the engineers around you while you do it. Key Responsibilities Set technical direction — shape platform and domain-level technical strategy that improves developer experience, reliability, security, and cost, and lead the high-complexity, cross-cutting initiatives that deliver it with measurable impact for the organization. Drive clarity through ambiguity. Take on the most loosely-defined problems, validate the critical assumptions early, and create alignment with stakeholders across teams so others can move quickly and confidently — driving cross-team decisions to a timely close and escalating when needed. Build the AI-augmented platform. Design org-wide tooling, guardrails, and policy-as-code that help every engineer get more out of AI-assisted development — infra primitives an LLM can safely reason about and PR against, automated review, and standards that hold as AI changes how code gets written. Own Infrastructure-as-Code standards for Kubernetes, AWS, and GCP using Terraform, Helm, Kustomize, and emerging tooling — setti

Your Career at Rubrik Rubrik (RBRK), the Security and AI Operations Company, leads at the intersection of data protection, cyber resilience, and enterprise AI acceleration. Rubrik Security Cloud delivers complete cyber resilience by securing, monitoring, and recovering data, identities, and workloads across clouds. Rubrik Agent Cloud accelerates trusted AI agent deployments at scale by monitoring and auditing agentic actions, enforcing real-time guardrails, fine-tuning for accuracy, and undoing agentic mistakes. For more information, please visit www.rubrik.com and follow @rubrikInc on X (formerly Twitter) and Rubrik on LinkedIn. About the Product Team The Product Team at Rubrik is responsible for driving Rubrik’s mission of securing the world’s data by creating products that simplify the complexity of managing cyber resilience across all applications and types of data. We seek to build consumer-grade experiences to solve the hardest and most complex enterprise challenges. What Product Growth, Specifically, Does at Rubrik Rubrik’s Product Growth team sits within product management and reports into Anneka Gupta, Chief Product Officer of Rubrik. Our team bridges Product Management, Analytics, and GTM Strategy to shape Rubrik’s monetization and business model vision. We are responsible for accelerating Rubrik’s business growth by identifying and unlocking levers across the customer lifecycle. Specifically, our team focuses on: Monetization & Packaging Strategy: Designing pricing models, tiering structures, and add-on packaging for core SaaS and AI products. Product-Led Growth & Adoption: Analyzing product telemetry and usage patterns to reduce friction, drive feature adoption, and accelerate time-to-value for customers. Expansion & GTM Alignment: Identifying cross-sell and upsell opportunities, optimizing packaging for new market segments, and aligning product capabilities with sales motions. Business Operations & Margin Optimization: Evalua

As a Lead AIOps Architect at Thoughtworks, you will be a hands-on technical leader driving engineering excellence and connecting our global AIOps capabilities with our regional client projects across APAC. As a seasoned AIOps practitioner, you will spend the vast majority of your time embedded in client project teams, designing production-grade solutions, writing high-quality code, and building automation pipelines on focused engagements. The rest of your time will focus on targeted technical pre-sales support, mentoring engineering teams, and advancing our internal AIOps practices. This is a high-visibility, technical individual contributor (IC) role. You will lead through technical influence, hands-on engineering, and architectural guidance across global and local teams, bringing global accelerators and reference architectures to local accounts while feeding project-level insights back to the global practice. Job responsibilities Architecture Design: Own the technical solution architecture for AIOps engagements, designing pragmatic, production-ready solutions that balance technical constraints, cost-efficiency, performance, and security. Hands-On Building: Deeply engage in building and implementing AIOps solutions, PoCs, and accelerators (across observability, intelligent alerting, AI-assisted triage, RCA, knowledge retrieval, and runbook automation) by writing production-quality code. Data & Workflow Engineering: Design and build data pipelines, tool integrations, and agentic workflows connecting observability, ITSM, and collaboration platforms into cohesive, automated flows. Engineering Excellence: Champion Thoughtworks engineering best practices, including clean code, TDD, CD, IaC, and strong observability within project teams. AI Evaluation & Governance: Design and operate evaluation/testing pipelines for AI/LLM components, establishing baselines/guardrails for accuracy, latency, cost, and reliability. Technical Advisory: Act as an AIOps advisor to cli

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Key Responsibilities 1. Solution architecture and design governance Own end-to-end architecture for assigned ServiceNow products — from discovery and design through release, adoption, and lifecycle improvement — producing artifacts such as blueprints, integration patterns, and decision records. Lead architecture reviews and design-authority forums for assigned products; approve designs within delegated authority and escalate enterprise-wide or exception decisions to the Platform Architect. Establish platform guardrails, reusable patterns, and coding/integration standards, and review internal and vendor designs for alignment, security, and technical-debt impact. 2. Demand intake, product ownership, and prioritization Serve as the functional/technical owner for assigned application areas and primary platform-facing partner to business Product Owners. Qualify and shape new ideas, enhancements, and technical debt into ready features, epics, and stories, using a transparent value-based prioritization method (e.g., WSJF). Represent assigned products in Demand Board, roadmap, and release/funding discussions. 3. Integration, data, CMDB/CSDM, and AI architecture Design integration approaches (IntegrationHub, APIs, events, MID Server) and define data ownership, quality, and lifecycle expectations for assigned products. Apply CMDB/CSDM, Service Graph, and service-modeling principles where relevant, and guide adop

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role We're looking for a Backend Engineer to join our Repository Management team within GitLab's Source Code stage. You'll help customers configure repositories with confidence so their GitLab projects support the way their teams work. As artificial intelligence agents increasingly write and manage code alongside people, you'll build guardrails that make development safe and trustworthy. You'll turn complex policy and repository management needs into reliable backend solutions that support people and the agents working on their behalf. You'll work in one of GitLab's oldest and most complex product areas, using

Role: DataOps Solution Architect — Azure Data Platform (Fabric & Databricks) Owns end-to-end architecture of the Azure data platform (Fabric, Databricks, Azure services) and sets the governance, security, and DataOps standards engineering teams implement. Design authority and primary architecture advisor to the client, not the day-to-day builder. Experience Required 8-10+ years overall in data engineering / cloud architecture, including 3+ years as a Solution Architect or in a comparable design-authority role. Microsoft Fabric: 2+ years hands-on. Azure Databricks: 4+ years hands-on. Proven track record designing and delivering enterprise-scale Azure data platforms end-to-end. Azure is mandatory ; experience across multiple client engagements or a consulting/SI background is a plus. Core Technical Expertise Azure Platform Fabric & Databricks architecture. ADF. ADLS. Entra ID. Key Vault. Monitor/Log Analytics. Microsoft Fabric Workspace & environment strategy. Lakehouse/Warehouse. OneLake. Pipelines/Notebooks. REST APIs/CLI. Governance. Azure Databricks Workspace strategy. Unity Catalog. RBAC. Jobs/Workflows. Delta Lake. Asset Bundles. ML platform integration. DevOps & IaC Azure DevOps/GitHub CI/CD. Terraform & Bicep. Branching/release strategy. Reusable IaC modules. Security & Networking Entra ID. RBAC architecture. Private Endpoints/DNS. Key Vault integration. DataOps Standards CI/CD & test gates for pipelines. Data-quality frameworks. Observability/alerting architecture. SLAs/SLOs. Incident-management practices. FinOps guardrails. Key Responsibilities Own end-to-end architecture; translate requirements into scalable, secure, cost-effective designs. Design enterprise-scale Fabric/Databricks architecture including workspace, networking, security, and governance. Set standards for CI/CD, IaC, DataOps, and environment management; ensure enterprise security and regulatory compliance. Evaluate technology options; identify architectural risks a

About the role As a Senior Software Engineer on the AI Enablement team, you will build the internal platforms, primitives, and guardrails that make AI a trusted co-pilot for employees across Chime. You’ll work on systems like Archimedes , Bosun , and easyRAG that power internal AI assistants, developer workflows, and retrieval-backed applications. These platforms make it easier for teams across the company to build, adopt, and scale LLM-powered tools safely and effectively. This team defines Chime’s golden paths for AI : opinionated but flexible patterns that help teams move quickly while maintaining safety, reliability, cost control, and governance. In this role, you’ll help turn emerging AI capabilities into durable, reusable platform features that can be adopted across the company. You’ll partner closely with Platform Engineering, Security, Risk, Legal, and product teams to build scalable, well-governed systems that support internal AI use cases from early prototyping through production adoption. In this role, you can expect to Build and evolve internal AI platforms such as Archimedes, Bosun, and easyRAG , enabling teams to develop and scale LLM-powered applications and workflows Design and implement reusable platform capabilities such as APIs, SDKs, templates, and shared services that make it easier to build safe, high-quality AI-powered tools Prototype and productionize new AI capabilities, identifying high-leverage use cases and turning successful patterns into durable platform features Define and improve Chime’s golden path patterns for LLM usage, balancing developer velocity with safety, reliability, and cost efficiency Develop systems that let teams launch AI-powered assistants and workflows in a standardized, observable, and governed way Establish evaluation, observability, and cost-management practices across AI systems, including quality, latency, safety, and spend Partner with Security, Risk, and Legal to implement practical guardrails for responsible A

About the opportunity As an IT Solutions Engineer (Google Cloud) within N26 Internal IT, you will be the primary architect, engineer, and guardian of our Google Workspace and Google Cloud Platform (GCP) corporate ecosystem. We aren’t looking for traditional system administrators. We need a modern, engineering-focused professional who treats our Google environment as a programmable platform. You will bridge the gap between corporate productivity, identity management, and cloud infrastructure—ensuring our global workforce is secure, highly automated, and empowered by next-generation AI integrations. In this role, you will: Infrastructure & Governance: Manage the full lifecycle of our enterprise Google Workspace organization. Design and maintain complex GCP project structures, organizational units (OUs), Cloud Identity, and Chrome Enterprise across the company. Automation & Development: Eliminate manual overhead by building robust, custom automation workflows. Leverage Google Apps Script, Python, and REST APIs to seamlessly integrate Workspace with internal tools, HRIS platforms, and Identity providers. Next-Gen Productivity: Lead the rollout, adoption, and ongoing optimization of Gemini Enterprise, driving organizational productivity through emerging AI capabilities. Security & Compliance: Design and enforce Data Loss Prevention (DLP) rules, Context-Aware Access (CAA), and secure BYOD (Bring Your Own Device) policies that balance "Security first" with "Employee Experience." eDiscovery & Compliance: Serve as the technical owner for Google Vault. Define and manage data retention policies, execute precise legal holds, and lead matter-based exports to meet strict financial regulatory and audit requirements. What you need to be successful: Google Workspace & GCP Expertise: Deep, hands-on experience administering Google Workspace at an enterprise scale, combined with solid foundational knowledge of GCP (IAM hierarchies, Service Accounts, VPCs, and Organi

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role We're looking for a Senior Frontend Engineer to join our Repository Management team within GitLab's Source Code stage. You'll help customers configure repositories with confidence so their GitLab projects support the way their teams work. As artificial intelligence agents increasingly write and manage code alongside people, you'll build guardrails that make development safe and trustworthy, turning complex policy and repository management problems into clear solutions for people and artificial intelligence agents acting on their behalf. You'll work in one of GitLab's oldest and most complex product areas,

About the Team Critical Harm Operations sits within User Safety & Risk Operations and builds enforcement systems for Frontier Risk and Material Harm that are accurate, fast, defensible, and built to scale. We turn policy intent into operational readiness, review standards, quality systems, escalation paths, automation guardrails, and durable cross-functional operating models. About the Role We are looking for an exceptional Program Manager to help build durable operating systems and run some of OpenAI’s most complex safety operations. The core need is a high-agency operator who can take an ambiguous problem, create the right structure, align cross-functional partners, and drive the work through execution. This role will move across Critical Harm priorities as needs evolve. You may step into operationalizing national security or violent-activities workflows, support wellbeing and Frontier Risk initiatives, or help scale programs such as Trusted Access. Deep domain expertise is helpful but not required; the strongest candidates will learn quickly, exercise excellent judgment, and make complex programs move. In this role, you will: Lead strategic operational builds across priority workflows from problem statement to implemented operating model, including scope, owners, milestones, risks, success measures, and execution cadence. Translate policy, safety, technical, legal, and operational constraints into workflows, requirements, playbooks, escalation paths, and decision-making structures that teams can execute. Coordinate with User Ops leadership, Product Policy, Integrity, Safety Systems, i2, Legal, Product, Engineering, Support, vendors, and other partners to resolve dependencies and keep critical work moving. Move in and out of workflows as priorities shift—standing up new programs, stabilizing operations, improving handoffs, and transitioning durable ownership to the right team. Use operational data and frontline signals to identify bottlenecks, quality gaps, ca

About the role As a Software Engineer on the AI Enablement team, you will contribute to the internal platforms, primitives, and guardrails that make AI a trusted co-pilot for employees across Chime. You'll work on systems like Archimedes, Bosun , and easyRAG that power internal AI assistants, developer workflows, and retrieval-backed applications. These platforms make it easier for teams across the company to build, adopt, and scale LLM-powered tools safely and effectively. This team defines Chime's golden paths for AI: opinionated but flexible patterns that help teams move quickly while maintaining safety, reliability, cost control, and governance. In this role, you'll build on and extend these patterns — shipping real features on production AI platforms while developing your depth in AI-specific engineering practices. You'll collaborate with Platform Engineering, Security, Risk, Legal , and product teams to build scalable, well-governed systems that support internal AI use cases from early prototyping through production adoption. In this role, you can expect to Contribute to and extend internal AI platforms such as Archimedes, Bosun, and easyRAG, helping teams develop and scale LLM-powered applications and workflows Build reusable platform capabilities such as APIs, SDKs, templates, and shared services that make it easier to develop safe, high-quality AI-powered tools Prototype and productionize new AI capabilities alongside senior engineers, turning successful patterns into durable platform features Apply Chime's golden path patterns for LLM usage, and help refine them as you deepen familiarity with the systems Build features that let teams launch AI-powered assistants and workflows in a standardized, observable, and governed way Learn and apply evaluation, observability, and cost-management practices across AI systems — including quality, latency, safety, and spend Partner with Security, Risk, and Legal to implement guardrails for responsible AI development and

The Cyber Deployment Manager partners with customers throughout the full lifecycle—from technical discovery and solution design through implementation, deployment, and adoption. You’ll work closely with Sales and Solutions Engineering during the pre-sales process to understand customer security priorities, assess technical requirements, develop solution architectures, and support demonstrations, workshops, and proofs of concept. After a customer commits, you’ll remain engaged as the technical deployment lead, translating the proposed solution into a production-ready implementation. You’ll guide integrations, establish success criteria, manage technical risks, and help customers operationalize AI across security workflows such as secure code review, vulnerability management, threat detection, incident response, SOC operations, and GRC automation. In this role, you will: Lead technical discovery with security executives, practitioners, architects, and engineering teams. Partner with Sales and Solutions Engineering on solution design, demonstrations, workshops, technical validation, and proofs of concept. Translate customer requirements into clear architectures, deployment plans, success criteria, and implementation milestones. Own the transition from pre-sales solution design into post-sales deployment and adoption. Serve as the primary technical partner during implementation, coordinating customer stakeholders and internal Product, Engineering, Security, and GTM teams. Build and troubleshoot integrations involving APIs, agents, security tools, cloud platforms, data sources, and enterprise workflows. Identify deployment risks, technical blockers, and product gaps, and drive them toward resolution. Help customers establish evaluation frameworks, governance controls, guardrails, monitoring, and human-review processes. Measure adoption and business impact, ensuring deployed solutions deliver meaningful security outcomes. Turn successful customer deployments into reusable

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. As a Senior Applied AI Engineer at Vanta, you will play a crucial role in shaping Vanta’s AI offerings, setting technical strategy, and leading projects that leverage AI to deliver smarter, faster outcomes for our customers. You'll be part of a team integrating AI into the Vanta product, working alongside a multidisciplinary group of product engineers, machine learning engineers, product managers, designers, and security and compliance experts to implement, scale, and maintain AI-enabled product experiences. In this role, you’ll build products that enable Vanta’s customers to leverage AI to accelerate their journey towards compliance, managing risk, and earning trust. Visit our Vanta Engineering Blog to learn more about what our team is working on! What you’ll do as an engineer working on Applied AI at Vanta: Work cross-functionally to design and implement AI-powered features to deliver customer value and integrate LLMs with Vanta’s existing products and systems. You’ll work with other product engineers across Vanta to understand how AI systems can accelerate product adoption at Vanta Instrument evaluations, guardrails, and monitoring, and review customer usage to continually improve quality Collaborate with AI Platform engineers shaping foundational AI systems and tooling that accelerate product teams Make pragmatic tradeoffs that consider business priorities, user experience, and a sustainable technical foundation Mentor engineers, champion good technical and product instincts, and model a collaborative, high-ownership engineering culture How to be successful in this role: At least 7 years of industry experience as a software