• Designing and building front-end interfaces for internal operational tooling, including dashboards, data observability views, and stakeholder communication surfaces • Developing rich data visualizations that surface pipeline health, data quality metrics, and business KPIs to technical and non-technical audiences • Building and maintaining backend services that support operational tooling, integrating with data infrastructure such as Snowflake, dbt, and monitoring platforms • Collaborating closely with data engineers, analytics engineers, and business stakeholders to translate data observability requirements into intuitive, high-quality interfaces • Working independently as a software engineer within a data-focused team, driving technical decisions for the tooling layer while leveraging other full stack teams across the organization for guidance and support • Shipping iteratively, balancing speed of delivery with code quality, maintainability, and scalability

• Take an active role in influencing the team roadmap and your own career development • Drive projects from initial ideation through implementation and into production operations • Design, build, operate, and maintain critical systems with a focus on reliability, performance, and availability • Build and maintain production backend services and APIs that support core customer and business workflows • Contribute to customer-facing and internal web applications, including our account and management portal • Design, build, and maintain integrations between Grafana systems and external business platforms such as NetSuite, Salesforce, and other third-party services • Work across internal services, APIs, and external systems to build reliable data flows and business-critical automations • Continuously improve the existing codebase by addressing technical debt, strengthening CI/CD pipelines, and increasing test coverage • Take ownership of the services your team runs, including participating in on-call rotations • Collaborate closely with engineers, product managers, and stakeholders across the company using async communication and regular video meetings • Work across one or more important AppCore domains, such as billing, provisioning, cloud marketplace integrations, account management workflows, and business systems integrations • Contribute to technical design discussions and help shape pragmatic solutions to business-critical problems • Embrace our open-source culture and contribute to projects that may not fall directly within your team’s immediate scope.

Role Description Softwarelösung im Microsoft-/Cloud-Umfeld. Unsere Zusammenarbeit findet vollständig im Home Office statt, mit kurzen Abstimmungswegen, hoher Eigenverantwortung und einer stark KI-gestützten Arbeitsweise. Für unser Entwicklungsteam suchen wir eine erfahrene Full-Stack-Entwicklerin oder einen erfahrenen Full-Stack-Entwickler mit Schwerpunkt auf React, TypeScript, .NET und Cloud-nativer Entwicklung. Die Rolle eignet sich besonders für Menschen, die Features ganzheitlich denken und gerne von der Datenbankschicht über Backend-APIs bis zur Benutzeroberfläche Verantwortung übernehmen. Wir nutzen KI-Tools konsequent im Entwicklungsalltag – von der Planung über Implementierung, Debugging und Code Reviews bis hin zu Dokumentation und Prozessoptimierung. Responsibilities - End-to-End-Feature-Entwicklung von der Datenbankschicht über REST APIs bis zur React-UI - Design und Implementierung responsiver React-Komponenten für Desktop und Mobile - Entwicklung skalierbarer Backend-APIs mit .NET 9, C#, FastEndpoints und Entity Framework Core - Arbeit mit React 19, TypeScript 5.9, Tailwind CSS, Radix UI, TanStack Router und TanStack Query - Integration mit Office.js, Microsoft Graph API und Azure Services - Umsetzung und Weiterentwicklung von Authentifizierungs- und Integrationsprozessen mit Azure MSAL - Mitarbeit an Datenbankdesign, SQL-Strukturen und Performance-Fragen - Cloud-native Entwicklung und Deployment auf Azure, unter anderem mit Azure Container Apps - Arbeit mit Docker, GitHub Actions, Elasticsearch, Redis, Azure OpenAI und Azure Service Bus - Aktive Mitwirkung an Code Reviews über den gesamten Stack - Mitgestaltung technischer Architekturentscheidungen - Aktive Nutzung von KI-Tools zur Steigerung von Qualität, Geschwindigkeit und Transparenz im Entwicklungsprozess Qualifications - Mindestens 5 Jahre Full-Stack-Erfahrung mit modernen Frameworks - Gute React- und TypeScript-Kenntnisse, inklusive React Hooks, State Management, REST APIs und responsiver Oberflächen - Sichere Kenntnisse in .NET, C#, REST APIs, Entity Framework Core und SQL - Gutes Verständnis für Datenbankdesign und SQL-Strukturen - Erfahrung mit Git, modernen Build-Tools wie Vite oder Webpack sowie DevOps-Grundlagen - Cloud-First-Mindset, idealerweise mit Azure oder alternativ AWS - Interesse an Microsoft-Technologien wie Office.js, Microsoft Graph API und Azure MSAL - Offenheit für KI-gestützte Entwicklungsprozesse und idealerweise praktische Erfahrung mit entsprechenden Tools - Sehr gute Selbstorganisation im Home Office - Proaktive und klare Kommunikation im Remote-Team - Strukturierte, pragmatische und lösungsorientierte Arbeitsweise - Gutes Gespür für die Balance zwischen schneller Lösung und langfristiger Wartbarkeit - Produktorientiertes Denken und Freude an der langfristigen Weiterentwicklung eines Softwareprodukts - Fließende Deutschkenntnisse Additional Qualifications - Erfahrung mit TanStack Router, TanStack Query oder Zustand - Office.js oder Office-/Outlook-Add-in-Entwicklung - Azure AD / Microsoft Entra ID oder Microsoft Graph API - FastEndpoints oder Minimal APIs - MediatR oder CQRS-Pattern - SignalR / WebSockets - Azure Container Apps, Azure OpenAI oder Azure Service Bus - Elasticsearch oder Redis - Docker und GitHub Actions - PostgreSQL und Performance-Optimierung - KI-Tools wie GitHub Copilot, ChatGPT, Claude, Cursor, Windsurf oder vergleichbare Werkzeuge - Gute Englischkenntnisse für technische Dokumentation und den Umgang mit Entwicklungsressourcen Benefits - 100 % remote aus dem Home Office - Flexible Arbeitszeiten mit gemeinsamer Erreichbarkeit ungefähr zwischen 10:00 und 16:00 Uhr - Teilzeit ab 20 Stunden pro Woche ist möglich, Vollzeit ist ebenfalls willkommen - Eine KI-First-Arbeitsweise mit konsequenter Nutzung moderner KI-Tools - Ein moderner Tech Stack mit React 19, TypeScript 5.9, .NET 9, PostgreSQL und Azure - Spannende Integrationen mit Office.js, Microsoft Graph und Azure OpenAI - Technologische Vielfalt durch tägliche Arbeit mit Frontend, Backend und Cloud-Services - End-to-End-Verantwortung von der Datenbank bis zur Benutzeroberfläche - Hohe Eigenverantwortung bei der Umsetzung neuer Features - Kurze Entscheidungswege und direkte technische Abstimmung - Die Möglichkeit, Architekturentscheidungen aktiv mitzugestalten - Ein pragmatisches, produktorientiertes Arbeitsumfeld ohne Konzernmentalität - Raum für eigene Ideen, Automatisierung und moderne Entwicklungsprozesse - Festanstellung mit Start zum nächstmöglichen Zeitpunkt - Standort Deutschland bevorzugt, EU nach Absprache möglich

Role Description GITI is seeking a Lead RF Software Engineer to support Cyber Operations Research and Development on passive RF emitter identification and network analysis from real-time sensor data streams. The candidate will implement, test, and maintain components of production software pipeline — a stream ingestion, rollup, and post-processing system operating on NDF (Network Description File) data produced by TDMA network sensors in dense, contested RF environments. Working under the direction of the Principal Engineer and the Technical Lead, the Lead RF Software Engineer supports Cyber Operations by contributing to pipeline development across a range of functional areas including: - Stream processing - Database integration - Display and reporting tools - Simulation infrastructure - CI/CD tooling The role requires strong Python skills, comfort with air-gapped Linux environments, and the ability to work independently on well-defined components with minimal supervision in support of real-world cyber operations. Responsibilities - Implement, test, and maintain assigned pipeline components including stream ingestion, rollup processing, database write, and batch post-processing modules in support of real-world cyber operations. - Develop and maintain browser-based visualization and reporting tools (track plots, waterfall displays, SmartBook report generation) that consume pipeline database output. - Implement and maintain stream simulation infrastructure, including TDMA network mission log replay and stream generation at controllable rates for pipeline testing. - Develop lightweight TNS simulator components: emitter and receiver models capable of following track plots and emitting in accordance with a network description. - Contribute to database integration work on tactical-box-spec hardware, including MySQL schema design, query optimization, and performance benchmarking. - Write comprehensive unit and integration tests for assigned components; implement and maintain CI/CD pipelines using GitLab to ensure functionality on hardware or in cloud environment. - Identify and report performance bottlenecks in Python pipeline components; assist with porting mature components to Rust or C as directed. - Perform basic Linux system administration on remote servers including package management, user configuration, and environment setup. - Manage source code using GitLab; follow disciplined versioning, branching, and code review practices as established by the Principal Engineer. - Produce clear technical documentation for implemented components including interface specifications, configuration guides, and test procedures. - Participate in periodic technical check-ins with the program technical lead; share findings and flag blockers promptly. Qualifications - Bachelor's (or equivalent) with 7-10 years of experience, or a Master's with 5-7 years of experience. Requirements - Strong proficiency in Python, with demonstrated experience in data processing pipelines, stream ingestion, or ETL development. - Proficiency with Python data science libraries including NumPy, Pandas (or Polars), and scikit-learn. - Experience with relational database development using MySQL, PostgreSQL, or SQLite, including schema design and query optimization. - Experience parsing or generating binary serialization formats (FlatBuffers, Protocol Buffers, or equivalent). - Ability to develop, test, and debug on remote Linux servers via SSH using command-line tools and a modern IDE. - Solid Linux operating system fundamentals including file system management, process control, and basic security hardening (Ubuntu). - Proficient in software engineering practices including Git/GitLab version control, unit testing, and CI/CD pipeline usage. - Experience developing browser-based data visualization or reporting tools, or demonstrated ability to learn React/D3-based tooling on the job. - Strong written and oral communication skills; ability to produce clear technical documentation for engineering audiences. - Ability to work independently on assigned components with minimal supervision in a small, distributed team. Desired Skills - Experience with TNS (Target Network System) sensor data formats and NDF ICD specifications. - Familiarity with TDMA network protocols, time-division access architectures, and passive RF signal processing concepts. - Experience with lightweight stream or message queue architectures (ZeroMQ, RabbitMQ, or equivalent). - Experience with Rust or Go for systems-level or performance-critical development on Linux. - Experience with Polars or DuckDB for high-performance analytical workloads. - Experience with performance profiling and optimization of Python pipelines on resource-constrained x86 hardware. - Experience with LLM-assisted software development tools (e.g., Claude Code, GitHub Copilot, JetBrains AI Assistant, or equivalent); demonstrated ability to use AI tools productively for code generation, refactoring, and test case development while maintaining engineering judgment and code quality standards. - Familiarity with AI/ML libraries (PyTorch, TensorFlow); ability to integrate trained model inference into a pipeline without requiring deep ML expertise. - Experience with Jupyter Notebooks and research enclave environments; ability to read and adapt research prototype code. - Experience with simulation or synthetic data generation for pipeline testing purposes. - Familiarity with Apache data science tools such as Spark or Dask for large-scale data processing. Relevant Certifications - Certifications in software engineering, computer science, or related fields (e.g., Certified Software Development Professional (CSDP); Certified Scrum Developer (CSD); Red Hat Certified Enterprise Application Developer; Certified Secure Software Lifecycle Professional (CSSLP); C++ Certified Associate Programmer (CPA); Professional Software Developer Certification (PSD); etc.)