Principal Cloud Platform Architect

Job Description: Principal Cloud Platform Architect

About KrateoSky

KrateoSky is building the trusted Western champion in AI aerial robotics—a unified perception and actuation platform that will make the skies the world's most trusted and transformative engine of productivity. We are not a drone company. We are the autonomy infrastructure powering robotic flight and aerial intervention across defense, industry, and public safety. We are executing a rapid roll-up strategy to consolidate best-in-class technologies, creating the first at-scale, AI-native alternative.

Speed and scale define our competitive advantage. We move fast by questioning assumptions, removing complexity, and rapidly demonstrating over analyzing. We scale by building certifiable platforms on reusable architectures. Our AI-native, digitally connected ecosystem amplifies this advantage, automating tedious work so engineers focus on novel problem-solving. We keep our back office small and our organization flat to maintain velocity and operate as one integrated team with real-time visibility into trade-offs, risks, and progress.

You're joining at the beginning when your decisions define how we scale to Western leadership. We're building a dream team of high performers to establish the processes, tools, and culture that enable rapid acquisition integration and platform scalability for missions that matter. No PowerPoint purgatory, no "that's how aerospace does it" sacred cows. First principles, data-driven decisions, hands-on execution.

Position Summary

Architect, secure, and operate KrateoSky's complete cloud infrastructure, data platform, customer-facing product cloud, and centralized SRE operations across Azure Commercial and Azure Government. Your mission is to build the segregated dual-use "red/green" cloud backbone that powers our next-generation AI perception and actuation platform while maintaining clear boundaries between commercial and government environments. This cloud architecture will ingest high-volume flight telemetry, drive scale-out MLOps pipelines and large data lake operations, support our agentic AI operating systems, enable fleet and device management at scale, and connect the end-to-end flight chain across drones, ground control stations, operator workflows, and cloud services with secure, high-throughput, low-latency data paths.

Senior hands-on IC role: You will be hands-on from day one. You must be comfortable doing the work yourself before you have a team to delegate to. We are looking for a builder who has shipped real systems—not PowerPoints, not just theoretical plans that never left the whiteboard. You think in systems but can get deep into the details when needed.

You are AI-native in how you work—AI assistants are your default environment. You generate boilerplate, infrastructure-as-code (IaC) configurations, automated deployment pipelines, synthetic load-testing harnesses, and security compliance scripts, and documentation with LLMs, and you use AI for autonomous cloud debugging, log analysis, and system architecture optimization. You see AI as the reason a small, elite team can outperform a traditional organization three times its size.

Embody our values and behaviors—deliver precision and quality, challenge how things are done, break problems into fundamentals, automate relentlessly, hold yourself accountable, and deliver together no matter the obstacles. You must exhibit Above the Line behaviors: operating as a Coach, Creator, and Challenger rather than a Victim, Hero, or Villain. You apply automation-first thinking: your default instinct is 'how do we eliminate this manual task' not 'who can I assign this to.' You act as a humble teacher, prioritizing ego-free knowledge sharing and documentation discipline. Finally, you maintain a strong PDCA (Plan-Do-Check-Act) orientation, demonstrating a willingness to experiment, learn from failure, and iterate.

Key Responsibilities

• Cloud Infrastructure & SRE Ownership: Own the architecture, security, and operation of KrateoSky's complete cloud footprint across Microsoft Azure Commercial and Azure Government. Drive the design and execution of our Infrastructure-as-Code (IaC) repository, AKS-based container platform, CI/CD pipelines, secure dual-use environment separation, identity and access architecture, secrets management, network segmentation, policy-as-code guardrails, and the core control plane for mission-critical cloud services.

• MLOps, Data Platform & AI Runtime Infrastructure: Own the cloud backbone for model training, retraining, evaluation, artifact and version management, feature/data pipelines, and large-scale data lake operations. Build the platform that supports both offline AI development and always-on agentic AI runtime services in production, with the security, lineage, and performance required for dual-use autonomy systems.

• Telemetry & Flight Chain Data Operations: Architect and operate the ingestion, transport, storage, and processing of high-volume flight telemetry, sensor streams, logs, and mission data flowing across drones, ground control stations, and cloud services. Design for bursty real-world traffic, intermittent connectivity, degraded field conditions, traceability, and operational resilience—not just clean lab conditions.

• Fleet & Device Cloud Architecture: Own the cloud-side architecture for fleet provisioning, device identity, certificate lifecycle, remote configuration, health monitoring, command routing, over-the-air update workflows, and remote diagnostics across connected aerial systems. Design for intermittent connectivity, safe recovery, and disciplined control of devices operating in the field.

• Customer-Facing Product Cloud & SaaS Architecture: Define and evolve the cloud control plane, customer-facing APIs, eventing and integration patterns, tenant isolation model, auditability, access control, and live-service reliability required for operators and customers to trust and run KrateoSky systems at scale.

• Platform Engineering & Developer Enablement: Build reusable internal platform services, paved-road deployment patterns, and self-service infrastructure capabilities that let engineering teams ship faster, observe better, and operate safely without re-inventing core cloud primitives.

• Platform Reliability, Observability & Governance: Establish SLIs/SLOs, observability, alerting, incident response, backup and disaster recovery, environment standards, and cost governance so teams can ship fast without creating architecture drift, reliability debt, or compliance exposure.

• AI-Native Execution: Make AI-augmented workflows the default; automate repetitive tasks; use AI for analysis, documentation, and error-catching; target 3-5x productivity gains over traditional approaches.

• AI-Native Use Cases:

  • Automated Infrastructure-as-Code Generation: Use LLMs (e.g., Cursor, GitHub Copilot) to generate complex Terraform/OpenTofu, Ansible, and Kubernetes manifest configurations, cutting infrastructure setup times from weeks to hours.

  • Self-Healing Infrastructure & Agentic SRE: Deploy AI agents to parse and monitor real-time cloud logs, predict performance bottlenecks, and trigger automated self-healing scripts for high-availability cloud platforms.

  • AI-Augmented Security & Compliance Guardrails: Automate control monitoring, evidence collection, policy drift detection, and continuous security posture management for environments aligned to SOC 2, CMMC Level 2, and FedRAMP requirements.

  • Telemetry Firehose Triage & Data Quality: Use AI agents to detect ingestion anomalies, dropped packets, schema drift, sensor data corruption, and pipeline bottlenecks across high-rate telemetry streams before they impact ML training, operational visibility, or customer-facing reliability.

• System Building & Documentation: Build processes from the ground up that are mature enough to be taught, documented, and replicated across future KrateoSky acquisitions.

• M&A / Technical Diligence Support: When relevant, assess acquisition targets for cloud infrastructure, DevOps maturity, and security compliance posture, and support post-acquisition migration and harmonization planning.

• Team Leadership & Culture: Start as a hands-on cloud/platform powerhouse of one; over time, build and lead a small high-caliber cloud infrastructure and reliability team as the platform scales. Set the bar for ownership, automation, operational discipline, and engineering craftsmanship.

• Cross-Functional Collaboration: Work closely with the Autonomy Software Capability Leader, the Head of Machine Learning, the Head of AI Innovation, the Chief AI Officer (CAIO), and the Chief Technology Officer (CTO) to ensure seamless cloud-edge integration, fleet-cloud reliability, audit-ready control implementation, robust cyber defense, and rapid, certifiable deployment capabilities across our unified autonomy platform.

Required Qualifications

• 10+ years of experience in DevOps, Site Reliability Engineering (SRE), Cloud Architecture, or Platform Engineering, with progressively increasing technical leadership in complex cloud environments—ideally within a dual-use company operating segregated commercial and government/defense cloud environments.

• Proven Track Record: You have a demonstrated history of architecting, building, and operating production-grade cloud platforms within a dual-use business model, including clear separation of data, identity, networks, and technical controls between commercial and government/defense environments. That includes real systems supporting MLOps, large-scale data operations, high-volume telemetry ingestion, fleet/device management, or customer-facing cloud products under operational pressure—not just standard enterprise IT, R&D/lab projects, or theoretical designs.

• Technical & SRE Depth: Deep hands-on expertise in Microsoft Azure architecture (Commercial + Government), Kubernetes/AKS, Infrastructure-as-Code (Terraform/OpenTofu), Entra ID / RBAC, secrets management, secure network architectures, observability, incident response, backup/disaster recovery, and live-service reliability. Fluent in streaming and ingestion pipelines (e.g., Kafka, Azure Event Hubs), scale-out MLOps infrastructure, large data lake operations, multi-tenant or customer-facing cloud architectures, and zero-trust platform design.

• Hard Operating Conditions: You have worked on cloud or platform systems that had to perform under real operational stress—high ingest rates, unreliable links, field deployments, regulated environments, mission-critical uptime requirements, or other non-ideal conditions. We are not looking for a generic cloud administrator for standard back-office workloads.

• AI-Native Proficiency: Advanced coding assistants (e.g., Cursor, GitHub Copilot) and modern LLM platforms (e.g., Claude, ChatGPT) are your default environment; you have achieved measurable productivity gains from AI-augmented IaC and script generation.

• Clearance Eligibility: Due to the nature of this role and the work performed, candidates must be eligible to obtain and maintain a U.S. Department of Defense Secret security clearance.

Desired Qualifications

• Experience at high-velocity startups or companies that have shipped at scale.

• Prior involvement in M&A cloud infrastructure due diligence or post-acquisition systems integration.

• Professional certifications in Azure Cloud Architecture or Kubernetes Administration (e.g., Azure Solutions Architect Expert, Certified Kubernetes Administrator) are highly desirable.

• Experience architecting and operating customer-facing cloud platforms for robotics, autonomy, IoT, geospatial, video, or other sensor-heavy systems in production is strongly preferred.

• Specific Industry Experience: Direct, hands-on experience implementing and operating the technical controls, evidence pipelines, and cloud architecture needed to support SOC 2, CMMC Level 2, and FedRAMP environments. Experience operating in CMMI-governed engineering organizations is a plus.

Logistics & Compensation

• Location: Remote (US-based)

• Reports To: Chief AI Officer (CAIO)

• Travel: N/A

• Compensation Range: $177,000 - $279,000 / year (Targeted base; total package includes comprehensive benefits)