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Were building foundational infrastructure to secure AI agents-including their identities, access patterns, and interactions with sensitive systems and data.
This includes designing intelligent, dynamic mechanisms for ephemeral access control, secrets management, and agent and user identity tailored to the modern agent ecosystem.
As the Manager, youll not only help define how agents authenticate, receive scoped access, perform actions securely, and leave behind a verifiable audit trail - youll also be responsible for building and leading a high-impact engineering team from the ground up.
This is a rare opportunity to combine hands-on engineering with technical leadership-writing critical code, mentoring engineers, sharing knowledge, and driving best practices-while building a platform from the ground up at the cutting edge of AI, identity, and security.
Responsibilities
Lead the end-to-end development of a secure platform for managing AI agents identities, permissions, access control, and execution context.
Recruit, onboard, and mentor a team of engineers, shaping the teams culture and technical direction.
Drive the design and implementation of core services, ensuring high performance, security, and maintainability.
Enforce engineering excellence and best practices, including testing, code reviews, observability, secure coding, and CI/CD pipelines.
Stay hands-on: actively contribute to critical paths in architecture, prototyping, and complex problem-solving.
Ensure your teams deliverables meet high standards of performance, resilience, and security in production.

Were building foundational infrastructure to secure AI agents - including their identities, access patterns, and interactions with sensitive systems and data. This includes designing intelligent, dynamic mechanisms for ephemeral access control, secrets management, and agent/user identity tailored to the modern agent ecosystem.
Youll help define how agents (both machine and human-facing) authenticate, obtain scoped access, perform actions securely, and leave a verifiable audit trail.
This is a unique opportunity to be part of a start-up inside the company - building the platform from scratch at one of the most cutting-edge intersections of AI, identity, and security.
Responsibilities:
Own the design and development of secure, scalable services that enable AI agents to manage their identities, secrets, and access - directly protecting critical systems and data.
Take charge of agent authentication flows and real-time access policies, ensuring seamless, reliable just-in-time, least-privilege access.
Lead the evolution of MCPs and agentic AI, transforming innovative ideas into systems that define how intelligent agents operate at scale.
Collaborate with architects and engineers to shape and deliver high-performance platform components you can take pride in.
Write clean, maintainable, and scalable code that powers some of the worlds largest and most security-conscious companies.
Drive cross-functional efforts with platform, AI, and security teams to gather requirements, influence design decisions, and bring impactful solutions to life.

Your Career:
Own and continuously improve AWS production infrastructure for scalability, reliability, security, performance, and cost.
Run and evolve Kubernetes environments that support fast, safe product delivery.
Drive developer velocity and production safety through better CI/CD pipelines, release workflows, deployment visibility, and GitOps practices.
Improve observability and incident response - reduce alert noise and raise signal quality.
Design and ship AI-assisted operational agents that change how engineers work - triaging monitoring alerts, summarizing incidents, proposing fixes, onboarding new services, answering questions and requests. This is a core part of the role, not a side project.
Build automation and self-service tooling that removes manual work from provisioning, monitoring, incident response, and developer workflows.
Analyze operational data across incidents, alerts, deployments, infra health, and cost to find reliability gaps, inefficiencies, and automation opportunities.
Partner with engineering, security, product, and leadership to remove bottlenecks and support safe production growth.
Evaluate and introduce new tools and AI-assisted approaches, balancing innovation with reliability, cost, and operational simplicity.
Your Impact:
You'll help scale production systems, improve deployment velocity and reliability, reduce operational overhead, and build automation and AI workflows that help engineering teams move faster and operate more efficiently.
This role is a strong fit for someone who enjoys ownership, collaboration, and operational innovation.

Help build an Always-On, low-overhead GPU profiling service that runs in production, scales across cluster environments, and delivers actionable insights for ML workloads. You will be hands-on delivering our profiling solutions across system software, drivers, and CUDA to make profiling continuously available and reliable.

What youll be doing:

Develop low-overhead, high-reliability implementations in C/C++, with bounded CPU/memory budgets.

Lead end-to-end feature delivery spanning user-mode components, driver/platform layers, and performance counter/trace providers.

Establish profiling models that integrate with existing ML/AI workflows (e.g., PyTorch/XLA) to turn low-level signals into actionable insights.

As a Senior or Principal Software Engineer in Cortex Cloud, you will contribute to the development and scaling of cloud-native security solutions for enterprise organizations. This role involves working within an established team to evolve a high-traffic product, with a focus on refining architecture, optimizing the technology stack, and maintaining engineering standards.
Your responsibilities include writing reliable code, influencing product direction, and designing distributed systems. You will be expected to make technical decisions that impact the long-term stability and performance of cloud workload protection services.
AI Integration & Engineering Workflow
A core component of our development process is the use of AI. Rather than basic code completion, we integrate AI assistants as functional components of our workflow. Our team utilizes a multi-agent AI system (IDEX/ProDex) that assists across the development lifecycle: from planning and architecture to code analysis and security reviews.
In this role, you will:
Work with AI Tools:Utilize platforms such asGemini, Claude, and Cursorfor tasks beyond code generation, including root-cause analysis, system design reviews, and architectural assessment.
Develop AI-Augmented Workflows:Help refine how AI is integrated into the SDLC, including the orchestration of agents and the development of internal tools that extend AI capabilities across our codebase.
Maintain Quality Standards:While AI assists in increasing velocity, you are responsible for the technical output. This includes critical review of all generated code and ensuring that AI-assisted work aligns with our architectural requirements and security benchmarks.
Interact with Specialized Agents:Coordinate with AI agents (Product, Architecture, Security) that operate on shared context to assist in managing complex engineering tasks.
We are looking for engineers who are interested in leveraging AI as a technical tool to manage complexity and who want to contribute to the practical application of human-AI collaboration in a cloud environment.

Cortex is expanding. We combine the high energy of a startup with the massive resources of the worlds cybersecurity leader. We aren't just processing data; we are managing hundreds of petabytes of it, waiting Cortex for you to apply your "magic" to invent the next generation of threat detection. As a Principal Software Development Engineer, you will be a cornerstone of the Cortex Detection Backend team. This role is designed for a technical powerhouse who thrives in the "sweet spot" between high-level architectural strategy and hands-on execution. You will influence our product roadmap, mentor elite engineers, and build systems that protect thousands of the world's most sensitive organizations.
Key Responsibilities
Architect & Innovate: Design and build a new set of capabilities focused on Data Analytics and Threat Detection. You will solve cloud security challenges that have never been tackled before.
Scale Without Limits: Ensure our microservices architecture remains robust and resilient under massive loads, processing millions of events per second.
Technical Leadership: Act as a technical sounding board and mentor. You will guide design discussions, conduct deep-dive research, and foster a culture of engineering excellence.
Strategic Collaboration: Work closely with Product Management, R&D leaders, and Security Researchers to define requirements and turn ambiguous problems into elegant technical solutions.
Drive Execution: Take ownership of the software development life cycle, ensuring high-velocity delivery in a fast-paced Agile environment.

Required Senior Software Engineer
Responsibilities:
Own, enhance, and improve our core platform
Build and maintain systems for collecting and processing metrics from client environments
Focus on system efficiency and resilient infrastructure
Integrate well-known SaaS platforms into our big data repository (e.g., major cloud providers, Datadog, Snowflake)
Optimize Spark and Airflow processes
Contribute to data design and platform architecture while working closely with other business units and engineering teams
Face the challenges of testing and monitoring large-scale data pipelines.

we are looking for an experienced Head of Architecture to lead the architectural vision and technical strategy for our platform. In this role, you will define and drive the long-term architecture of our Threat Exposure Management platform, ensuring scalability and innovation as we continue to grow exponentially.
WHAT YOU WILL DO

Define and lead the overall architecture strategy of Zafrans platform.

Design scalable, secure, and resilient distributed systems.

Partner with Engineering leadership to guide technical direction and architecture decisions across teams.

Lead the design of complex cross-platform integrations with security tools and enterprise environments.

Ensure architectural consistency, performance, and scalability as the company grows.

Mentor senior engineers and architects and help elevate engineering standards across the organization.

Evaluate and introduce new technologies, frameworks, and architectural patterns.

Drive architectural reviews and ensure best practices in system design, reliability, and security.

We seek a versatile Senior Software Engineer who is passionate about performance optimization and generative AI. Our team brings the latest research in LLM inference - from novel decoding strategies to quantization schemes - into production across our hardware lineup, from large data center servers to powerful edge devices. We work on the most advanced architectures in the field, with a focus on NVIDIA's own.

What you'll be doing:

Implement and optimize inference algorithms for LLM and omnimodal architectures, including hybrid Mamba-Transformer and mixture-of-experts models.

Profile inference pipelines using NVIDIA's profiling and simulation tools. Correlate simulation predictions against real hardware across data center and edge devices.

Write and tune GPU kernels (CUDA, Triton) for operators like fused MoE layers, SSM state updates, and quantized GEMMs.

Solve distributed inference problems: expert parallelism, communication-compute overlap, collective tuning, multi-node deployment.

Build production-grade software inside major open-source libraries - vLLM, SGLang, Dynamo, FlashInfer.

Own optimization features end-to-end, from scoping through delivery, collaborating with research, product, and engineering teams worldwide.

As an Engineering Manager at Cortex Cloud, you will lead a team of ~6 engineers operating in one of our most complex and cross-functional domains. This role requires a strong blend of people leadership and deep technical expertise, including systems design and large-scale distributed cloud architectures. You will be responsible for driving the design and delivery of complex, high-impact systems, while ensuring the team executes against the roadmap with both speed and engineering rigor.
Key Responsibilities
Build, mentor, and lead a high-performing software engineering team, fostering a culture of empowerment and driving both individual growth and collective impact.
Partner closely with Product Management and cross-functional teams (Infrastructure, Research, UX) to define priorities and shape multi-quarter product roadmaps, ensuring alignment across all stakeholders.
Own the end-to-end software development lifecycle, translating product strategy into executable plans and ensuring consistent, high-quality, on-time delivery.
Provide architectural leadership for scalable, distributed systems operating at petabyte scale, guiding the design and implementation of high-throughput, cloud-native backend microservices.
Drive production readiness by enforcing best practices around deployment, observability, reliability, and runtime stability, focusing on the details to ensure operational excellence.
Align stakeholders across business units through clear communication of technical strategy, trade-offs, priorities, risks, and execution plans.
Engage directly with strategic customers to lead technical deep dives and architecture reviews, and to influence future product direction.
Foster a culture of high engineering standards, accountability, and continuous improvement, with a strong emphasis on quality and security.

In this role, you will act as the primary architect of the "nervous system" that bridges the gap between sophisticated AI models and real-world business logic. You will design and maintain the critical infrastructure that enables intelligent, autonomous features to function reliably at scale, moving beyond simple API wrappers to build deeply integrated AI systems. You will take ownership of the entire data flow, where you will develop high-performance RAG (Retrieval-Augmented Generation) pipelines and complex agentic workflows that provide users with accurate, context-aware responses.
Your Impact
Champion system stability by implementing rigorous evaluation and monitoring frameworks, ensuring that as our AI capabilities grow, our production environment remains fast, cost-effective, and secure.
Ultimately, you will be the technical force that transforms cutting-edge AI research into stable, scalable products that define the future of our platform.

We are hiring a Senior Software Engineer to join the NSV tools group. You will craft high-performing software automation systems used in NVIDIA's Data Center environments. This involves our AI cluster topology generation platform that composes, configures, and validates network infrastructure behind large-scale AI clusters. You will collaborate with NIC, OS, Switch, HCA, CPU, and GPU compute teams, along with architects, network engineers, and developers. We support data growth for the worlds biggest companies. Our worldwide engineers work in a dynamic, meaningful, and fast-paced setting. Are you ready for the challenge?

What you'll be doing:

Build and develop a full-stack automation platform (Python microservices backend, modern web frontend) used to generate, configure, and validate network topologies for AI/HPC data centers.

Implement scalable, reliable, and maintainable services and APIs that turn complex infrastructure requirements into validated, exportable network configurations.

Build and refine intuitive web interfaces that guide users through an interactive, step-by-step topology development workflow.

Collaborate closely with internal and external collaborators to understand requirements and deliver robust full-cycle solutions.

Improve stability and performance across the generation pipeline through architectural improvements and code optimizations.

Troubleshoot issues in distributed, containerized environments and contribute to system observability and reliability improvements.

Work cross-functionally with architects, DevOps engineers, product managers and collaborators to ensure high-quality releases.

Participate in code reviews, technical design discussions, and continuous improvement activities within the team.

We're looking for a Senior Software Engineer, Infrastructure & Automation to join and play a key role in building the engineering infrastructure behind our AI-powered offensive security platform.

You'll design and build the infrastructure required to automatically validate and improve our platform and agents, including AI-powered agents for testing, evaluating, and automation of our systems that ensure our platform infrastructure and AI agents perform is reliable, repeatable, and effective at scale. Working closely with our AI Research, Security Research, and Engineering teams, among other things, you'll develop the infrastructure that enables rapid experimentation, deterministic validation, and continuous evaluation of autonomous AI attackers.

If you're excited about building developer platforms, testing infrastructure, and complex distributed systems in a fast-moving AI startup, we'd love to meet you.

Responsibilites
Design and build the testing and automation infrastructure that powers Tenzais platform and autonomous security agents. Define and shape the platform architecture for that goal.
Build deterministic and indeterministic validation tools for platform behavior and repeatable, data-driven evaluation for non-deterministic agent behavior.
Help develop continuous evaluation pipelines that measure performance, compare models and releases, detect regressions, and surface actionable results.
Build Python services and automation that orchestrate distributed test runs and manage their environments, inputs, and results.
Create internal tools and agents and CI/CD integrations that improve experimentation speed, developer productivity, and release confidence.
Partner with AI Research and Security Research to define evaluation methodologies, success criteria, and coverage.
Own systems end to end - from architecture and implementation through production reliability and continued evolution.
Contribute to technical design, architecture discussions, and code reviews across the engineering organization.

we care deeply about performance, clarity, and building tools that feel right. Were a small team of engineers who enjoy solving hard backend problems and working close to the data. If you're into Go, value clean architecture, and love building for other developers - this might be a great fit.

What Youll Do

Build high-performance backend systems in Go
Work on real-time data pipelines and large-scale telemetry infrastructure
Tackle tough challenges in distributed systems, scale, and performance
Collaborate with infrastructure, frontend, and product teams to ship features end to end

We are looking for an experienced QA engineer to lead and drive the Quality of our cloud sensor - the industrys most efficient security tool for monitoring application-layer attacks in real time.

we are a fast-growing cybersecurity startup transforming how organizations protect their applications, cloud environments, and AI systems at runtime. Backed by top-tier investors including Greenfield Partners, Red Dot Capital Partners, Lightspeed, Ballistic Ventures, and TLV Partners, were on a mission to make real-time security a reality.

As our Sensor Quality Lead, youll own the quality of the Sensor - how we test it, and how we prove it works accurately and efficiently across the environments our customers run it in. There's no existing playbook for this role; you'll be the one writing it, tackling complex testing challenges in the Linux systems realm and building the automation that lets us ship with confidence.

In particular:

Design and build automated test frameworks and specialized harnesses for the Sensor
Build and maintain test environments across Kubernetes, Docker, and VMs, including test applications written in different languages, so a single build is validated everywhere it runs
Build the test infrastructure that measures accuracy, performance, and resource consumption under high scale
Define quality metrics for the Sensor, build the test infrastructure that measures them along with dashboards and visibility measures to surface them
Collaborate with the Sensor teams, Product Managers, research, and other R&D teams to deliver end-to-end quality