Top Software Engineer Jobs in Berlin

Design, build, and operate production-grade generative AI systems: multi-agent orchestration, end-to-end RAG pipelines, LLM evaluation and integration, scalable AWS-based AI infrastructure, CI/CD for models, observability, data validation, and evaluation frameworks to ensure quality, attribution, and resilience.

Own, design, and develop the AI Data Platform: maintain a high-scale data product platform (≈400K pipeline jobs/month, petabyte scale), architect cross-cloud data infrastructure, build and operate automated data pipelines, ensure data observability and quality, and implement AI-driven features and AI data agents to expose AI-ready data products.

Design and build automated testing frameworks, pipelines, and validation tools for a cloud-native, microservice insurance platform. Develop integration, end-to-end, and regression tests, improve CI/CD quality gates, investigate production issues, and collaborate across engineering and product teams to ensure system correctness, reliability, and observability.

Design, build, and operate backend services and LLM orchestration pipelines. Implement RAG/agent flows, CI/CD, schema migrations, observability, secure multi-tenant access, and participate in on-call incident response to ensure reliable production systems.

Design, build, and operate backend microservices that integrate carriers end-to-end. Implement event-driven pipelines (Kafka/SQS), ingest and normalise carrier events, design resilient third-party clients (REST, SOAP, EDI, SFTP), model data in MongoDB/MySQL, and deploy containerised services on Kubernetes in AWS.

Build and maintain services and tooling to automate and secure network lifecycle across data centers. Implement CI/CD, staged rollouts, drift detection, observability pipelines, and APIs that integrate network source-of-truth with the cloud platform. Collaborate with network engineers and SREs to turn operational pain into production-grade automation and tooling.

Work on YDB distributed storage and database systems to maximize performance on modern and legacy hardware (NVMe, HDD, DPUs). Reengineer components for low-latency, high-throughput workloads, profile and debug production systems, and design resilient distributed storage primitives. Collaborate on incident resolution and production deployments to support Nebius cloud services.

Work on Percona's open-source MongoDB operational tools (primarily ClusterSync and also Backup). Build and harden a Go-based replication engine handling initial cloning and continuous change streams, ensure correctness and fault tolerance at scale, support sharded clusters, optimize performance and resource usage, and maintain CLI/HTTP APIs, metrics, logging, tests, and packaging. Collaborate openly via GitHub pull requests and JIRA.

Design, build, and operate backend systems that power the incident lifecycle: automated AI ingestion/detection agents, validation/conflation algorithms, and delivery APIs. Collaborate with cross-functional teams and MapGPT, test and monitor services, reduce technical debt, be on-call, and drive product-focused distributed systems at scale.

Develop and maintain ClickHouse Cloud interfaces and dashboards, collaborating with cross-functional teams while ensuring code quality and scalability.

Develop core backend components for a blockchain network, focusing on networking, reliability, scalability, and high-quality software practices.

Develop and enhance front-end, server-side, and database applications, focusing on blockchain products while ensuring high performance and security.

Dragonfly is seeking Software Engineers for various portfolio companies, focusing on crypto technologies. Engineers of all experience levels are needed across multiple stacks.

As a Distributed Systems Engineer, you'll design and evolve LiveKit's core systems, implement resilient architectures, and enhance reliability and developer velocity, working on critical features in production environments.

The Senior Infrastructure Engineer will manage and scale LiveKit's core infrastructure, focusing on reliability and performance, while working on Golang code and automation for distributed systems.

Design and evolve core control, data, and observability systems; implement resilient region-spanning architectures; build libraries, protocols, and tooling; diagnose and harden critical paths using metrics, tracing, and testing; and shape platform capabilities across identity, scheduling, observability, and distributed state management.

Design, implement, and manage LiveKit's infrastructure, focusing on performance, reliability, and automation while ensuring effective incident management and coordination with vendors.

The role involves designing and evolving core systems at LiveKit, implementing resilient architectures, and building tools to enhance system reliability and developer speed. Strong distributed systems experience and programming skills are essential.

Design, implement, and operate low-latency, highly available distributed control, data, and observability systems. Build region-spanning architectures, libraries, protocols, and tooling; diagnose and harden critical paths using metrics, tracing, testing, and real traffic; and shape platform capabilities around identity, scheduling, observability, and distributed state management.

Provide hands-on technical leadership across the department: design and deliver mid-to-large systems, integrate autonomous agents into the SDLC, drive architecture and operational improvements, mentor engineers, partner with product and leadership, and influence organizational technical strategy to enable payments/fintech solutions.

The role involves designing, developing, and operating high-throughput streaming data pipelines, ensuring system quality and performance, and collaborating with engineering leaders to enhance Mapbox's telemetry capabilities.

As a Staff Software Engineer, you will lead the development of Apache Iceberg, enhancing data handling capabilities for large-scale systems, collaborating with teams, and architecting solutions for modern data lakes.

Lead the development of Runware's serverless platform by building core systems for AI workload management and providing technical guidance to the team.

The Senior Software Engineer will design and implement systems for AI integration, build scalable backend services, and mentor team members, ensuring high-quality systems that meet user needs.

As a Senior Software Engineer, you will develop and manage a MongoDB solution on various platforms, ensuring reliability and security while contributing to a small team focused on impactful projects.