Backend Software Engineer, AI/ML (m/f/d)

About the Role

Crewmeister is a fast-growing workforce management software provider, part of the ATOSS Group. We are investing in engineers to help shape the future of software development, combining strong engineering fundamentals with AI-powered workflows, tools, and product capabilities. This role is for experienced backend software engineers focused on building scalable backend systems and pushing the boundaries of AI-enabled product development. It is not a machine learning research or AI specialist role. The primary focus will be designing, building, and operating reliable, scalable, and observable services that enable AI-powered functionality at enterprise scale.

Location: Bangalore (Whitefield, ITPL)

Work Model: Hybrid with a minimum of 50% office attendance. Daily office attendance is expected in the Bangalore office during the first six months for onboarding, collaboration, and team integration. After the onboarding period, the role transitions to the standard hybrid working model.

Key Responsibilities

• Design, build, and operate backend services and APIs that power AI-driven and traditional product capabilities within the ATOSS platform.
• Develop high-quality production software using Java, and secondarily Python, with a strong focus on reliability, maintainability, and performance.
• Own services end-to-end, from architecture and implementation through deployment, monitoring, and ongoing operations.
• Integrate LLMs, AI agents, and retrieval-based solutions into production applications.
• Build and improve evaluation, monitoring, and observability capabilities for AI-powered features.
• Contribute to CI/CD pipelines, deployment automation, and engineering best practices.
• Help ensure AI-powered systems are scalable, secure, and production-ready.
• Troubleshoot complex production issues and drive continuous improvements in system reliability and performance.
• Work closely with AI Engineers, Product Owners, and Cloud Operations teams to bring new capabilities into production.

Technology Stack

Our team works with a modern AI and cloud-native technology stack including Java, Python, AWS, EKS, Docker, Kubernetes, LangGraph. You'll work on the Cognitive Backend platform that powers AI-driven capabilities across our products, at the intersection of AI Engineering and core platform development.

Requirements & Tech Stack

Mandatory

• Strong experience building backend applications with Java.
• Strong experience designing, building, and operating APIs, services, and distributed systems in production environments.
• Proficient Python skills for automation, integrations, and AI-related development.
• Hands-on experience with cloud platforms such as Azure, AWS, or GCP, as well as modern CI/CD practices and containerized applications using Docker.
• Strong understanding of monitoring, logging, and observability, with a focus on building reliable and maintainable systems.
• Practical experience building, integrating, deploying, or operating AI-powered applications, LLM-based solutions, retrieval systems, agentic frameworks, or similar technologies in a professional environment.

Preferred

• Experience with frameworks such as LangChain, LangGraph, CrewAI, or similar technologies for building AI-powered applications.
• Familiarity with vector databases such as Pinecone, Weaviate, Milvus, Chroma, or pgvector.
• Experience working with Retrieval-Augmented Generation (RAG) architectures and AI evaluation frameworks such as Ragas, Promptfoo, or similar tools.
• Hands-on experience with Kubernetes, ideally within Azure Kubernetes Service (AKS) environments.
• Experience with Infrastructure as Code using Terraform or similar technologies.
• Experience building multi-tenant SaaS platforms or enterprise software products.

Why Crewmeister

• Join one of Europe's fastest-growing SaaS companies.
• Help shape the future of AI-enabled software development.
• Work on meaningful products used by thousands of businesses.
• Be part of a collaborative engineering culture focused on learning, ownership, and continuous improvement.