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About the Role

We’re looking for a motivated Agentic AI Engineer Intern to join our Z1Agent team. This is a great opportunity to learn how production Agentic AI applications are designed, built, and run.

What is Z1Agent?

Z1Agent is an open-source, autonomous AI-driven K8s incident-resolution and root-cause analysis engine combining L1 cluster triage, L2 telemetry reconstruction/correlation, and L3 deep OS level diagnostics through a pluggable agent/tool architecture. It uses LLM reasoning, agentic workflows, and causal analysis to diagnose failures and generate verified remediation actions.

It also implements a continuous ML lifecycle: production telemetry and incident data are curated into training/evaluation datasets, models are fine-tuned and benchmarked, and validated weights are automatically deployed, creating a closed-loop MLOps pipeline for continuously improving diagnosis and remediation.

Responsibilities

  • Develop and maintain backend services and REST APIs using Python3
  • Implement CRUD operations and integrate them with relational and NoSQL databases
  • Assist in building and integrating AI/ML features (e.g., model inference APIs, LLM-based workflows)
  • Write clean, testable, well-documented code
  • Containerize applications using Docker
  • Help deploy and manage services on Kubernetes clusters
  • Debug issues, monitor services, and troubleshoot performance problems
  • Collaborate with engineers in code reviews, stand-ups, and sprint planning

Required Skills

  • Python 3: Strong fundamentals (data structures, OOP, error handling, virtual environments)
  • AI basics: Understanding of core AI/ML concepts, and familiarity with libraries or tools such as scikit-learn, PyTorch, TensorFlow, or LLM APIs
  • REST APIs: Knowledge of HTTP methods, status codes, authentication, and API design; experience with FastAPI, Flask, or Django
  • CRUD operations: Hands-on experience building Create, Read, Update, Delete functionality end to end
  • Databases: Understanding of how databases work, including:
      – SQL (PostgreSQL / MySQL): joins, indexing, normalization, transactions
      – NoSQL (MongoDB / Redis): when and why to use them
      – Basic query optimization and schema design
  • Docker: Ability to write Dockerfiles, build images, and run containers
  • Kubernetes: Working knowledge of pods, deployments, services, and configuration (ConfigMaps/Secrets)
  • Git: Comfortable with version control and pull-request workflows

Good to Have

  • Experience with cloud platforms (AWS, GCP, or Azure)
  • CI/CD basics (GitHub Actions, GitLab CI, Jenkins)
  • Familiarity with Linux and command-line tools
  • Knowledge of message queues (Kafka, RabbitMQ)
  • Exposure to vector databases and RAG pipelines
  • Basic understanding of monitoring tools (Prometheus, Grafana)
  • Personal projects, open-source contributions, or a GitHub portfolio

Qualifications

  • Currently pursuing or recently completed a Bachelor’s/Master’s in Computer Science, IT, or a related field
  • Strong problem-solving skills and eagerness to learn
  • Good communication and teamwork skills

What You’ll Gain

  • Hands-on experience with production-grade AI and backend systems
  • Mentorship from experienced engineers
  • Exposure to modern DevOps and cloud-native practices
  • Opportunity for a full-time offer based on performance
  • Internship certificate and letter of recommendation

About the Role

We’re looking for a motivated Software Engineer to join our Z1Compliance team, with strong Linux security skill and OS internals knowledge to help build and enhance our security and compliance platform.

What is Z1Compliance?

Z1Compliance is a developer-focused security and compliance platform that continuously scans infrastructure, detects security and compliance gaps, and helps automatically turn findings into fixes.

We build an automated security and continuous compliance platform call Z1 Compliance. We continuously monitor Linux/macOS host machines to detect vulnerabilities, track configuration baselines, and support regulatory compliance.

Role Overview

We are looking for a Software Engineer Intern who wants hands-on experience building production software across the full stack.

In this role, you will work on core platform features, building backend APIs in Python (FastAPI) and Go, working with system-level agents (osquery and shell automation), querying high-throughput databases (PostgreSQL and ClickHouse), and contributing to our React / TypeScript dashboard.

Key Responsibilities

  • Backend API Development: Develop backend services in Python (FastAPI) and Go that power device enrollment, authentication, and compliance data ingestion.
  • Endpoint & Linux Automation: Help build and maintain lightweight agents and installer scripts (Bash / Shell) that run on Linux/macOS machines and interface with system monitoring tools like osquery.
  • Data Management & Analytics: Write and maintain database queries in PostgreSQL (relational configuration data) and ClickHouse (high-volume security telemetry and event logs).
  • Frontend Dashboard: Collaborate on user-facing features in our React + TypeScript web application (fleet views, agent settings, and security status tables).
  • Testing & Debugging: Diagnose and fix issues across host services, logs, and database records, writing unit and integration tests to ensure platform stability.

Requirements

  • Education / Background: Degree in Computer Science, Software Engineering, or equivalent practical project experience (final-year students and recent graduates are encouraged to apply).
  • Programming Skills: Proficiency in Python or Go (working knowledge of both is a strong plus). Basic practical experience with JavaScript / TypeScript and React.
  • Linux Fundamentals: Comfortable using Linux terminal commands, inspecting running processes, managing file permissions, and writing basic shell scripts.
  • Databases & APIs: Familiarity with relational databases (SQL, schema design) and REST API principles.
  • Engineering Mindset: Good problem-solving skills, ability to read system logs to trace bugs, and an eagerness to learn cloud and security tooling.

Nice to Have

  • Exposure to endpoint tools like osquery or general systems monitoring concepts.
  • Familiarity with columnar databases (like ClickHouse) or message queues (like Kafka).
  • Basic experience with Docker and containerized environments.
  • Knowledge of web security concepts (JWT, TLS/HTTPS, authentication flows).
  • A GitHub profile showcasing personal or university software projects.

About This Role

We’re looking for a motivated Platform Engineer (Intern) to join our Z1Sandbox team. This is a great opportunity to learn on workload orchestration, secure execution, deployment automation, and fleet management across large-scale Kubernetes clusters, leveraging MicroVMs and gVisor for workload isolation and security.

What is Z1 Sandbox?

Z1Sandbox is a high-security, multi-tenant Sandbox execution platform. This is a great opportunity to learn  on workload orchestration, secure execution, deployment automation, and fleet management across large-scale Kubernetes clusters, leveraging MicroVMs and gVisor for workload isolation and security.

What You Will Work On (Responsibilities)

As a Platform Engineering Intern, you will work hands-on with real distributed systems and live Kubernetes clusters. You will:

  1. Kubernetes Multi-Cluster Automation:
    • Assist in modernizing platform scripts into 100% declarative Kubernetes controllers, Custom Resources, and Helm templates.
    • Maintain and test Open Cluster Management (OCM) hub-to-spoke workload distribution (ManifestWork, ManagedCluster lifecycle, taints, and placement rules).
  2. Database Replication & Split-Brain Safe Failback:
    • Monitor and validate CloudNativePG (CNPG) physical streaming replication, WAL timeline progression, and schema consistency.
    • Implement declarative Kubernetes Job resources for delta synchronization across divergent cluster states.
  3. Gateway & Ingress Routing:
    • Configure, test, and optimize our Envoy Active-Passive Proxy running on WireGuard overlay meshes (ports 80 and 6443).
    • Write automated end-to-end chaos tests (killing primary control planes, simulating network partitions, and verifying sub-second failover).
  4. Sandboxed Workload Execution:
    • Test and optimize security sandbox execution on worker spoke nodes using gVisor (runsc), Kata Container and Kubernetes Resource Pools.
  5. Observability & Operational Tooling:
    • Build Grafana dashboards and Prometheus metrics for replication lag, proxy latency, and cluster failover triggers.
    • Maintain clear architectural runbooks and automated validation scripts.

Technology Stack You Will Use

  • Orchestration: Kubernetes, KinD, Open Cluster Management (OCM), Helm 3
  • Networking & Ingress: Envoy Proxy, Gateway API, WireGuard mesh, MetalLB
  • Data & Caching: PostgreSQL (CloudNativePG Operator), Valkey / Redis, RabbitMQ
  • Workload Security: gVisor runtime (runsc), Containerd, kata container
  • OS & Virtualization: Linux, Docker
  • Automation & Scripting: Bash, Python, YAML, GitOps

Minimum Qualifications

  • Enrolled in or recently graduated with a degree in Computer Science, Software Engineering, Information Technology, or equivalent practical experience.
  • Solid foundational understanding of Linux operating systems (systemd, process management, file permissions, basic networking like IP, DNS, routing).
  • Familiarity with Docker and container fundamentals (building images, volume mounts, container networking).
  • Basic working knowledge of Kubernetes core concepts (Pods, Deployments, Services, ConfigMaps, Namespaces).
  • Proficiency in Bash scripting and at least one programming language (Python, Go, or JavaScript/TypeScript).
  • Strong debugging mindset, curiosity to understand why distributed systems fail, and a methodical approach to documentation.

Nice-to-Have (Bonus Points)

  • Prior experience deploying applications with Helm.
  • Hands-on exposure to database replication concepts (master-replica, WAL, failover).
  • Familiarity with reverse proxies (Envoy, NGINX, or HAProxy).
  • Experience working with multi-cluster Kubernetes or KVM virtual machines.

What You Will Learn & Career Growth

  • True Production Distributed Systems: Move beyond toy single-node projects to production-grade multi-cluster topologies.
  • Disaster Recovery & High Availability: Master how enterprise platforms survive catastrophic outages with zero data loss.
  • Cloud-Native Networking: Deeply understand Layer 4/Layer 7 traffic routing, mTLS, and overlay networks.
  • Mentorship & Portfolio Building: Direct mentorship with senior engineers, working on an architecture that serves as an impressive portfolio piece for top-tier DevOps/SRE roles.

About the Role

We are a fast-growing AI infrastructure company building cutting-edge GPU cloud platforms and high-performance inference solutions that empower AI developers, startups, and enterprises worldwide. As we scale our global operations, we are looking for a skilled and hands-on AI Infra Engineer – SRE (Kubernetes) to join our Global Infrastructure team.

Role Overview

This is a critical hands-on position focused on the reliability, performance, and operational excellence of large-scale, high-performance AI/ML GPU clusters in our data centers. As an AI Infra Engineer – SRE (Kubernetes), you will design, operate, and optimize Kubernetes-based infrastructure to ensure maximum uptime, efficiency, and scalability for demanding AI workloads. You will bring deep expertise in system-level troubleshooting, GPU cluster management, and automation to keep our platforms running at peak performance.

Key Responsibilities

  • Design, build, and maintain scalable, production-grade AI/ML infrastructure using Kubernetes.
  • Proactively monitor GPU cluster health, performance, and utilization across compute, accelerators, storage, and networking layers, performing root-cause analysis and resolution.
  • Develop and implement automation for infrastructure provisioning, configuration, and ongoing management.
  • Own the complete GPU node lifecycle — including provisioning, dynamic scaling, maintenance, decommissioning, and zero-downtime upgrades of GPU-enabled nodes in Kubernetes environments.
  • Build and improve CI/CD pipelines for reliable infrastructure deployment and orchestration.
  • Enforce security best practices, compliance standards, and operational excellence across the infrastructure stack.
  • Lead incident response and post-incident improvements for issues related to GPUs, CPUs, high-speed storage, and networks.
  • Manage end-to-end customer GPU resource provisioning — from request intake and configuration to onboarding, troubleshooting, and support — ensuring high levels of customer satisfaction.
  • Stay up to date with the latest GPU hardware, software, and orchestration technologies, integrating relevant advancements into our platforms.
  • Be available for occasional regional or international travel to data center locations as required.

Requirements

  • Bachelor’s degree in Computer Science, Engineering, or a related technical field.
  • 3+ years of practical experience in data center operations, infrastructure engineering, or site reliability engineering.
  • Strong background in infrastructure automation using tools such as Terraform and Ansible.
  • Deep hands-on experience with Kubernetes in large-scale environments, including:
    • NVIDIA GPU Operator for GPU driver management, device plugins, container toolkit, and monitoring (DCGM).
    • NVIDIA Network Operator for high-performance networking, RDMA, and GPUDirect support.
    • CNI (Container Network Interface) and CSI (Container Storage Interface) plugins tailored for AI/ML workloads.
    • Integration with job schedulers such as Slurm in Kubernetes clusters.
  • Proficiency in Linux system administration and scripting (Python, Bash).
  • Experience with observability stacks including Prometheus, Grafana, and Loki.
  • Solid understanding of GPU architecture, NVIDIA CUDA, NCCL, and AI/ML frameworks is a strong plus.
  • Excellent troubleshooting skills with the ability to analyze complex system logs and performance metrics.
  • Strong communication and collaboration skills to work effectively with engineering and operations teams.

Reports To: Director of Cloud Infrastructure

Role Overview:
Join our Core Kubernetes Operator Development team, where we’re pushing the boundaries of Kubernetes innovation. As a Kubernetes Controller Developer (Golang), you will play a crucial role in building “01”, our cloud-agnostic Platform as a Service (PaaS), driven by full-fledged Kubernetes operators and agents.

This position requires a strong background in Kubernetes internals and Golang programming, particularly in developing and managing Kubernetes controllers. If you’re a proactive problem solver with experience in building cloud-native infrastructure, this is your opportunity to contribute to a transformative platform.

We highly encourage candidates with a solid programming foundation and a hunger to explore the cloud-native world to apply. Comprehensive onboarding and professional development support will be provided.

Key Responsibilities (Not limited to):

  • Collaborate in Agile teams, taking ownership of development stories with minimal supervision.
  • Partner with internal teams and clients to accurately capture technical requirements.
  • Design, build, deploy, and maintain Kubernetes controllers and operators using Golang.
  • Identify gaps in current systems and propose or implement technical improvements.
  • Apply best practices across the full software development lifecycle.
  • Create and execute unit, regression, and E2E tests for operator reliability.
  • Work in Linux environments and troubleshoot issues in containerized applications.
  • Contribute to CI/CD workflows for seamless testing and deployment.

Essential Skillset:

  • Kubernetes Controller Development: Proven expertise in building and maintaining controllers and operators.
  • Proficiency in Golang: 2+ years writing idiomatic, well-tested Go code for Kubernetes projects.
  • Deep understanding of Kubernetes APIs and libraries including client-go, CRDs, and API extensions.
  • Hands-on experience with:
    • Kubebuilder – For scaffolding controllers and CRDs
    • Operator SDK – For building Operators with OLM support
    • controller-runtime – For abstracting Kubernetes client logic
  • Strong testing skills, including unit, load, and E2E tests for operators.
  • Familiarity with containerization (Docker) and orchestration (Kubernetes).
  • Comfortable working in Linux with debugging tools and CLI.
  • 2+ years experience working with CI/CD tools like Jenkins, GitHub Actions, Tekton, or similar.

Preferred Skills (Nice to Have):

  • CKA or CKAD certifications.
  • Hands-on experience managing production-grade Kubernetes clusters.
  • Knowledge of Infrastructure as Code tools (e.g., Terraform).
  • Exposure to major cloud providers: AWS, GCP, or Azure.
  • Scripting experience in Shell or Python.

What We Offer:

  • A chance to build infrastructure automation tools that power real-world workloads.
  • Opportunity to work on bleeding-edge cloud-native technologies with a global impact.
  • Collaborative and innovation-driven culture, with strong engineering mentorship.
  • Remote-friendly setup and flexible work culture.
  • Career development in one of the most in-demand areas of DevOps.

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