Pragmatike

DevOps Engineer

• Operate and maintain large-scale Linux infrastructure across Debian/Ubuntu-based bare-metal and virtualized environments
• Own MAAS-based bare-metal provisioning, including region/rack controllers, PXE, commissioning, cloud-init, node lifecycle, and API/CLI automation
• Operate and maintain production Kubernetes clusters, including upgrades, node pools, networking, storage, security hardening, and troubleshooting
• Design and maintain multi-site networking across VLANs, L2/L3 routing, bonded interfaces, VPNs, firewalls, and DNS
• Automate infrastructure provisioning and operations using Ansible, Bash/Python, OpenTofu/Terraform, and Git-based workflows
• Build and maintain automated deployment workflows including PXE, Preseed, and cloud-init
• Operate observability platforms using Prometheus, Grafana, Alertmanager, VictoriaMetrics/VictoriaLogs, or comparable tooling
• Define and improve SLIs, SLOs, alerting, and reliability practices across infrastructure and platform services
• Lead infrastructure incident response, troubleshooting, escalation, and post-incident improvements
• Maintain on-call processes and operational coverage across distributed environments
• Work close to the hardware layer, including IPMI/Redfish, BMCs, RAID, storage, hardware diagnostics, and GPU infrastructure
• Manage virtualization platforms including Proxmox, KVM/libvirt, OpenStack, or VMware, including GPU passthrough where required
• Build and maintain internal infrastructure tooling for host discovery, configuration, IPAM, hardware health, and operational automation
• Own infrastructure lifecycle activities including site onboarding, maintenance, decommissioning, drift detection, and operational runbooks
• Work closely with engineering and cross-functional teams to improve reliability, resource utilization, and operational efficiency

Senior Site Reliability Engineer – MAAS

Security Operations

• Develop, implement, validate, tune, and maintain security monitoring and detection capabilities
• Administer and optimize SIEM platforms across multiple customer environments
• Manage security detection rules and use cases throughout their lifecycle
• Onboard, integrate, test, and validate new security data sources and telemetry feeds
• Review and improve detection logic, security content, and monitoring configurations
• Collaborate with Threat Intelligence and Incident Response teams to translate threats into actionable detection capabilities
• Support cybersecurity architecture reviews and provide recommendations to improve security monitoring
• Build and maintain security metrics, dashboards, KPIs, and service-performance reports
• Evaluate detection effectiveness and identify opportunities to reduce false positives
• Contribute to quality assurance, process reviews, control validation, and corrective actions
• Maintain SOC procedures, standards, documentation, knowledge bases, and operational guidance
• Prepare technical reports, findings, and recommendations for internal and external stakeholders

Security Operations Analyst – SIEM, Threat Detection

• Monitor, triage, and investigate security alerts across SIEM, EDR, Microsoft security tools, and cloud platforms
• Analyze host and network logs from Windows, Linux, databases, applications, web servers, firewalls, and NIDS/HIDS
• Investigate suspicious activity and identify potential root causes
• Support incident response, remediation, and recovery activities
• Determine appropriate escalation paths and coordinate with relevant cybersecurity teams
• Work with Incident Response specialists to investigate and manage threats
• Identify opportunities to improve detection quality and reduce false positives
• Support security monitoring optimization and whitelist tuning
• Prepare technical reports, summaries, and security findings
• Maintain SOC documentation, procedures, and knowledge-base content
• Contribute to process improvements and operational quality initiatives

Security Operations Analyst – Cyber Defense

• Monitor, triage, and investigate security alerts across SIEM, EDR, Microsoft security tools, and cloud platforms
• Analyze host and network logs from Windows, Linux, databases, applications, web servers, firewalls, and NIDS/HIDS
• Investigate suspicious activity, identify root causes, and determine appropriate remediation or escalation
• Support incident response, remediation, and recovery activities
• Work closely with Incident Response and other cybersecurity teams to manage security threats
• Analyze network and security events using TCP/IP, syslog, firewall, and network monitoring data
• Identify opportunities to improve detection quality and reduce false positives through tuning and optimization
• Gather technical information from clients to improve security monitoring and detection
• Prepare and present security reports, summaries, and technical findings
• Contribute to SOC procedures, documentation, knowledge bases, and quality-control processes
• Review operational feedback and implement corrective actions to continuously improve service quality

Security Operations Analyst – Cyber Defense Operations

Frontend Engineer

• Build and maintain the product UI using React and TypeScript for agent inventory, policy management, session investigation, and security dashboards
• Build data-dense interfaces including timelines, graphs, tables, filtering, and search across large datasets
• Optimize frontend performance when rendering and interacting with large volumes of security data
• Collaborate with Go backend engineers on REST and gRPC-web APIs
• Collaborate with design teams on interaction patterns
• Own frontend quality across component architecture, accessibility, testing, and performance
• Contribute to the shared design system and frontend tooling
• Use AI-assisted development workflows to accelerate implementation, testing, debugging, and problem-solving
• Participate in interviews discussing real-world AI use in software development and validation of AI output

UI Developer – Agentic Security Platform

Machine Learning Engineer

• Design, train, and evaluate threat detectors using classifiers, embedding-based models, fine-tuned LLMs, and rule/ML hybrid approaches
• Build and maintain training and evaluation datasets, labeling workflows, and benchmark suites
• Track model performance through precision/recall, error analysis, drift, and adversarial robustness
• Serve models in production under strict latency requirements
• Build inference services in Go and integrate them with gateway and endpoint pipelines
• Optimize inference performance and cost through quantization, distillation, batching, and caching
• Work with security researchers to turn emerging attack techniques into training data and detection logic
• Build and maintain MLOps workflows for reproducible training, model registries, monitoring, and safe model rollouts
• Use AI-assisted development workflows for implementation, testing, debugging, and experimentation

ML Engineer – Threat Detection Models

AI Engineer

• Design and build LLM-powered analysis and classification pipelines, then productionize them as Go services
• Prototype approaches in Python, including prompting strategies, RAG, structured extraction, and ML classifiers
• Ship solutions that meet defined accuracy targets
• Define ground-truth datasets, evaluation metrics, and regression suites to continuously measure and improve model quality
• Monitor model quality and drift in production and build processes to identify and address degradation
• Collaborate with security researchers to translate attack patterns and risk signals into detection and summarization logic
• Integrate AI-powered capabilities with event, storage, and UI layers to surface actionable results to security teams
• Use AI-assisted development workflows to accelerate implementation, testing, debugging, and experimentation
• Participate in interviews discussing real-world AI use in software development, validation of AI output, and changes to working practices

AI Engineer – Agentic AI, Cloud Discovery

Product Manager

• Own the roadmap, requirements, and prioritization for the product area from discovery through launch
• Lead customer discovery with CISOs, security architects, and cloud/AI platform teams
• Translate customer needs into clear problem statements and PRDs
• Partner with engineering and security research on scope, technical trade-offs, and delivery
• Participate in technical design reviews
• Define success metrics and measure adoption, coverage, and detection effectiveness
• Work with product marketing, sales engineering, and support on positioning, enablement, and launches
• Track the evolving AI security landscape, including agent frameworks, LLM providers, regulation, and competitors
• Translate relevant AI security developments into product strategy
• Use AI tools and agentic workflows for research, analysis, documentation, and daily product work
• Own either the Cloud Discovery workstream, building an inventory of AI agents, models, and AI-enabled applications across customer cloud environments, or the AI Security Platform workstream across gateway, agentic security, forensics, or shared platform capabilities

Product Manager – AI Security

Backend Engineer

• Design, build, and operate production Go services with high standards for performance, reliability, and multi-tenancy
• Design APIs and data models, owning service contracts, idempotency, retries, and back-pressure
• Build event-driven pipelines and integrations with cloud providers, internal systems, or AI/agent frameworks
• Own service reliability through testing, observability, CI/CD, and production readiness
• Use Python for tooling, testing, migrations, automation, or data workflows
• Collaborate with AI engineers, security researchers, and product teams on threat models and enforcement logic
• Use AI coding assistants as part of daily development, testing, and debugging workflow

Backend Engineer – Go, AI Security Platform

Technical Writer

• Own end-user, administrator, and API documentation for the AI security platform from initial structure through ongoing maintenance
• Create deployment and integration guides for gateway, endpoint, cloud discovery, and platform components
• Include code samples and configuration references
• Write release notes and in-product help
• Maintain documentation standards and style guidelines
• Generate and maintain API documentation from OpenAPI and protobuf definitions with engineers
• Keep documentation aligned with product releases
• Review technical examples and documentation for accuracy, consistency, and usability
• Gather customer and Support feedback to identify documentation gaps and improve clarity
• Use AI tools to draft, review, update, and maintain documentation at scale while validating technical content
• Collaborate with engineers, Product Managers, Support, security researchers, customers, and distributed product teams

Technical Writer – AI Security Platform

• Design and build Go agents and backend services for endpoint visibility and security enforcement across Windows, macOS, and Linux
• Detect AI applications, local models, browser-based agents, and IDE assistants
• Monitor endpoint interaction with sensitive files and processes
• Build backend services for endpoint fleet management, configuration, policy distribution, telemetry ingestion, and health monitoring
• Optimize endpoint software for low resource usage, reliability, safe updates, and resilience on unreliable networks
• Collaborate with security researchers on detection logic and platform teams on telemetry and data pipelines
• Contribute to cross-platform testing, code signing, release engineering, and production readiness
• Use AI-assisted development workflows for implementation, testing, debugging, and problem-solving
• Discuss real-world AI usage, validation of AI output, and AI’s impact on work during interviews

Backend Engineer – Go, Endpoint Security

Financial Planning and Analysis

• Act as Finance Business Partner to commercial, operations, and product teams
• Build and maintain financial simulation models, including business plans, unit economics, and deployment scenarios
• Model and present ROI and TCO of infrastructure deployments directly to clients and partners throughout the sales cycle
• Own monthly financial reporting, profitability analysis by site or unit, and KPI tracking
• Track margin, cash conversion, and payback period
• Contribute to budgeting and forecasting
• Challenge operational assumptions in partnership with business teams
• Analyze manufacturing and deployment cost structures for infrastructure units
• Identify optimization levers with industrial and production teams
• Prepare financial materials for executive committee, board, and investors
• Support due diligence for fundraising or asset financing
• Collaborate with finance teams across group operating companies to ensure consistency of models and consolidated reporting