myneva

Platform Engineer

• Architect and scale the backbone of our AI Platform
• Ensure high availability, low latency, and seamless integration of machine learning capabilities into production
• Own the microservices that power AI inference
• Build robust multi-tenant infrastructure
• Support our Data & AI team with production-grade DevOps practices
• Design, build, and maintain Go microservices that handle AI model inference
• Architect scalable APIs (gRPC/REST) for production applications
• Own the Kubernetes infrastructure (EKS)
• Implement service-to-service communication using gRPC and message queues
• Integrate with cloud AI services (AWS Bedrock, OpenAI, Anthropic)
• Build multi-tenant capabilities including authentication, rate limiting, usage tracking, and tenant isolation
• Partner with the Data & AI team to productionize machine learning models
• Build comprehensive observability: structured logging, metrics, and alerting
• Implement CI/CD pipelines and infrastructure-as-code for automated deployments
• Ensure high availability through monitoring and incident response
• Optimize resource utilization for GPU workloads and cost-efficient scaling strategies

AI Platform Engineer

Frontend Engineer

• Contribute to the development of a new web-based product within the myneva portfolio
• Build intuitive, reliable, and maintainable user interfaces supporting complex workflows
• Use modern frontend technologies, collaborating with backend engineers, product management, and UX
• Take ownership of frontend features and continuously improve code quality
• Apply modern engineering practices, including effective use of AI-supported development tools
• Design and implement frontend components using React and TypeScript
• Collaborate closely to deliver cohesive end-to-end user experiences

Software Engineer – Frontend

Backend Engineer

• Design and implement scalable, maintainable backend and fullstack components using .NET / C#
• Design APIs and integration solutions within a complex software ecosystem
• Guide decisions around data modeling, persistence, and performance trade-offs
• Design for reliability, scalability, and observability in distributed systems
• Collaborate closely with product management, UX, and engineering peers
• Ensure high code quality through testing, reviews, and standards

Senior Software Engineer – Backend / Fullstack, .NET / C#

• Design and evolve the application and integration architecture of a new web-based product
• Design and own core backend and API components using .NET / C#
• Set technical standards and ensure scalable, maintainable implementations
• Guide architectural decisions considering security, data protection, and regulatory requirements
• Work hands-on in development and act as a technical role model
• Lead and mentor engineers through reviews, coaching, and technical decisions
• Enable responsible and effective use of AI-supported development tools
• Collaborate closely with product management and neighboring teams

Senior Software Engineer – Tech Lead, .NET / C#

• Implementieren Backend- und ausgewählte Fullstack-Komponenten mit .NET / C#.
• Wirken an der Entwicklung von APIs und der Integration von Services in einer modularen Systemlandschaft mit.
• Setzen zuverlässige Datenzugriffs- und Persistenzmuster um.
• Beteiligen an der Implementierung von Features und ausgewählten End-to-End-Funktionalitäten.
• Nutzen KI-gestützte Entwicklungstools für Coding, Refactoring, Testing und Dokumentation.
• Überprüfen und bewerten KI-generierte Ergebnisse kritisch.
• Tragen durch automatisierte Tests, Dokumentation und Code-Reviews zur Codequalität bei.
• Arbeiten eng mit anderen Entwicklern, Product Management und UX zusammen.

Junior Software Engineer – Backend / Fullstack, .NET / C#

DevOps Engineer

• Design and maintain container-based deployment setups using Docker and related technologies.
• Define repeatable deployment and runtime models across cloud and hybrid environments.
• Build and maintain deployment and environment automation to ensure reliable and auditable operations.
• Support development teams with CI/CD pipelines, deployment automation, and release processes.
• Design and improve observability solutions for reliable operations.
• Advise on infrastructure topics such as networking, security, hardware requirements, and scalability.
• Collaborate closely with development and product teams to ensure operability is considered early.
• Use AI-assisted tools to improve operational efficiency while validating their outputs.

Senior DevOps Engineer

• Contribute to the development of a new, strategically important web-based product within the myneva portfolio
• Work on backend and selected fullstack components delivering reliable, scalable, and maintainable software solutions
• Collaborate closely with engineers, product management, and UX to implement features with clear ownership
• Apply established engineering practices and contribute to technical quality
• Actively support the continuous evolution of the product, including the responsible use of AI-supported development tools

Software Engineer – Backend, Fullstack, .NET, C#

• We are looking for a Go Platform Engineer who thrives at the intersection of infrastructure, AI systems, and DevOps.
• In this role, you will architect and scale the backbone of our AI Platform: Ensuring high availability, low latency, and seamless integration of machine learning capabilities into production.
• You will own the microservices that power AI inference, build robust multi-tenant infrastructure, and support our Data & AI team with production-grade DevOps practices.
• Design, build, and maintain Go microservices that handle AI model inference, data processing pipelines, and real-time streaming workflows.
• Architect scalable APIs (gRPC/REST) that serve as the bridge between AI models and production applications.
• Own the Kubernetes infrastructure (EKS), including deployments, autoscaling policies, service mesh, and cluster health monitoring.
• Implement service-to-service communication using gRPC and message queues (RabbitMQ/SQS) for asynchronous processing.
• Integrate with cloud AI services (AWS Bedrock, OpenAI, Anthropic) and manage model serving infrastructure.
• Build multi-tenant capabilities including authentication (JWT/JWKS), rate limiting, usage tracking, and tenant isolation.
• Partner with the Data & AI team to productionize machine learning models—wrapping them in production-ready services with proper health checks, circuit breakers, and graceful degradation.
• Build comprehensive observability: structured logging, metrics (Prometheus), distributed tracing (Jaeger/Tempo), and alerting.
• Implement CI/CD pipelines and infrastructure-as-code (Terraform) for automated deployments and disaster recovery.
• Ensure high availability through proper monitoring, incident response, and post-mortem analysis.
• Optimize resource utilization for GPU workloads and cost-efficient scaling strategies.

Senior AI Platform Engineer

QA Engineer

• Design, implement, and maintain automated tests for frontend and backend components
• Implement automated API tests and contribute to contract testing
• Ensure automated tests are integrated into CI/CD pipelines
• Analyze test results and support root cause analysis
• Use AI-assisted tools for test generation and analysis
• Work closely with Engineering, Product Management, and UX