Top Software Engineer Jobs in Berlin

Design and ship production iOS features for AI-powered travel and expense experiences. Build Swift-first applications using modern concurrency, SwiftUI, networking, offline storage, and real-time APIs. Create conversational and context-aware UX, integrate LLM-driven capabilities, optimize performance and privacy, and use analytics and experimentation to improve products. Collaborate with product, design, and backend teams while maintaining a well-tested, high-quality codebase.

Build and maintain backend services, APIs, and event-driven workflows for Navan’s expense platform. Develop AI agents, receipt intelligence, document extraction, and conversational expense features while improving accuracy, latency, cost, observability, and safety. Work with financial data requiring idempotency, auditability, permissions, and reliable partial updates. Partner with Product and Design, contribute to web and mobile experiences, write technical designs, review code, and mentor teammates.

Build and operate software integrations connecting CuspAI’s AI platform with partner laboratories. Develop APIs and data models, integrate instruments, robotics, LIMS/ELN systems, and scheduling tools, and ensure reliable data exchange through retries, queues, monitoring, and alerting. Support partner onboarding, deploy containerized cloud services, and collaborate with materials scientists and engineers to create scalable closed-loop discovery workflows.

Develop and operate fullstack software for logistics automation and warehouse management. Build backend-heavy services integrating conveyor systems, parcel sorters, transport robots, and warehouse business logic. Responsibilities include requirements refinement, design, coding, testing, deployment, monitoring, incident handling, and collaboration with product and engineering teams. The role uses Java and Spring Boot alongside Vue.js, Node.js, microservices, databases, event-driven systems, cloud tooling, and AI-assisted development tools.

Build customer-facing applications that make complex account information clear and interactive. Develop React and TypeScript experiences integrated with Python and Golang backends, troubleshoot issues, review code and architecture, create tools and libraries, document integrations, and maintain reliability through automated testing. Collaborate with product, design, and other cross-functional teams in a customer-focused, agile environment.

Develop and maintain cloud-based applications using C# and .NET. Design microservices, distributed architectures, and REST APIs; containerize applications with Docker and Kubernetes; and contribute to Azure DevOps CI/CD pipelines. Work with SQL Server, Entity Framework, MongoDB, testing frameworks, authentication, authorization, caching, and modern software design principles. Contribute to solution architecture, APIs, continuous improvement, client onboarding, consulting, and technical knowledge-transfer initiatives.

The Software Engineer will develop AI-based capabilities, maintain software stacks, mentor others, and tackle engineering challenges across various technical fields.

Develop and operate backend-focused advertising content systems and Content Studio tooling for Zalando partners. Build APIs, event-driven services, and campaign content features; decompose requirements into deployable tasks; write maintainable, tested code; collaborate with product and business stakeholders; and implement observability, alerting, and operational support for production systems.

Build and maintain reusable quality engineering frameworks, tooling, libraries, and automation. Integrate automated checks into CI/CD pipelines, improve test infrastructure, investigate failures across systems, and create guardrails that strengthen feedback loops. Collaborate with engineering, DevOps, and data teams to improve testability, diagnostics, reliability, and maintainability. Enable delivery teams to adopt and maintain effective quality practices through shared tools, documentation, and hands-on support.

Build and improve Databricks platform features across backend, full-stack, infrastructure, databases, cloud, systems, tools, and customer-facing products. Own the full software development lifecycle, including design, development, testing, and production operations. Develop reliable, scalable, and secure solutions while collaborating with engineering teams, receiving mentorship, and contributing to impactful projects.

Build and maintain internal applications, data workflows, integrations, APIs, automation, and engineering tools. Own moderately complex features from design through testing, deployment, documentation, and handover. Collaborate with scientists and business teams to translate needs into reliable software, improve code quality, add testing and observability, and apply secure, maintainable engineering practices across multiple projects.

Develop and operate MAIA, a generative AI platform featuring agent systems, RAG pipelines, external-system integrations, and knowledge search. Own features from concept through continuous improvement, integrate and evaluate language models, improve performance and reliability, and build secure isolated execution environments. The role requires strong backend engineering, practical LLM experience, product thinking, agentic development, security awareness, and proactive remote communication. No people management responsibility is required.

Build and maintain MotherDuck’s cloud database platform and DuckDB integrations using systems programming. Own projects involving dual execution, dynamic resource assignment, distributed execution, database performance, and reliability. Collaborate with frontend, platform, infrastructure, support, and DuckDB Labs teams; diagnose production issues, improve architecture, document expertise, mentor teammates, and contribute to the DuckDB open-source community.

Build scalable, resilient, and fault-tolerant backend products as part of a client engineering team. Responsibilities include developing APIs and SaaS services, working with Go and cloud platforms, maintaining distributed systems, deploying with Docker and Kubernetes, applying testing and TDD practices, optimizing performance, and evaluating AI tools to improve engineering impact. The role requires strong communication, collaboration, problem-solving, and pragmatic technology decision-making.

Design and build scalable Python backend and cloud systems that integrate AI and LLM capabilities into production applications. Responsibilities include developing AI services, architecting AWS deployments, extending Terraform infrastructure and CI/CD pipelines, implementing testing and monitoring, and creating agentic workflows with orchestration frameworks such as LangGraph. The role collaborates across teams to deliver reliable AI-driven products and requires strong software engineering, cloud infrastructure, and problem-solving skills.

Build, test, deploy, and maintain scalable web and mobile applications. Own features from concept through launch while collaborating with Product, Design, Data Science, and engineering teams. Apply automated testing, strong code quality practices, relational database and schema design expertise, analytical problem-solving, and user-focused design. Work within agile methodologies and contribute to continuous deployment, production monitoring, knowledge sharing, and ongoing engineering improvement.

Develop and maintain high-performance Rust and Python simulation and validation frameworks for autonomous air systems. Build Software-in-the-Loop and Hardware-in-the-Loop environments, automated testing, fault injection, regression coverage, and deployment infrastructure. Collaborate with autonomy and systems teams, optimize real-time simulation performance, maintain documentation and benchmarks, review code, mentor colleagues, and improve reliability, safety, and operational performance.

Senior backend engineer building and operating cloud-native microservices for client authentication, KYC, GDPR-compliant flows, and Salesforce integrations. Write testable, secure Java/Kotlin code, deploy on AWS (ECS, Fargate, Lambda), own services end-to-end, and improve engineering excellence, CI/CD, and observability.

Lead rapid end-to-end prototyping of LLM-powered agent systems: build working prototypes, design experiments measuring quality/latency/cost/user impact, validate with users, produce reference implementations, and hand off to product teams to inform roadmap decisions.

Lead front-end development for partner-facing financial web products, including embeddable onboarding modules, partner dashboards, and self-service workflows. Build complex multi-step forms and data-heavy interfaces with React and TypeScript, contribute to Node.js server layers, collaborate on API contracts, and work closely with product, design, and backend teams. Own features from design handoff through production release while maintaining multiple codebases and upgrading business-account APIs.

Design, develop, maintain, test, and improve native iOS and iPadOS applications using Swift. Collaborate with distributed teams and product managers to build features, conduct code reviews, resolve bugs, automate quality assurance, and enhance user engagement. Contribute transparently to Mozilla’s open-source community and support product experiments and improvements.

Build and enhance a high-scale, highly concurrent cloud platform supporting video streaming, analytics, data storage, and IoT communication. Improve system stability, scalability, and security while introducing new technologies. Design distributed backend systems, data streaming architectures, RESTful APIs, and integrations across AWS and diverse data stores. Apply strong testing practices and contribute to responsible AI tooling and model integration.

Build and own Python backend services for Grover’s real-time risk decisioning platform. Develop rule engines, decision APIs, dynamic pricing, counteroffers, third-party risk integrations, and Kafka event-driven workflows. Improve reliability, observability, and production operations while collaborating with risk analysts, data scientists, and product teams. The role includes on-call support, service debugging, AWS infrastructure, analyst tooling, and LLM-powered risk assistance.

Design, build, and optimize GPU-accelerated deep learning inference software and frameworks (e.g., SGLang, vLLM). Profile and tune LLM and Generative AI model serving across NVIDIA accelerators, contribute code to inference libraries, and collaborate across teams to deploy high-performance multi-GPU solutions.

Develop Rust-based cloud integration features that create, manage, and adapt cloud resources across Kubernetes environments. Collaborate on architecture, infrastructure, and feature design; use AI to improve development quality and speed; and work directly with users to gather requirements and debug distributed systems. The role requires production Rust experience, strong systems thinking, cloud-native knowledge, and familiarity with backend infrastructure tooling in a remote-first startup.