Backend Software Engineer - AI/ML (m/f/d)
Builds and operates Java (secondarily Python) backend services on AWS/Kubernetes that power AI features — LLMs, agents, RAG — across Crewmeister's workforce-management SaaS. Day to day: designing scalable APIs, integrating AI capabilities, and running observable, production-ready services from the Bangalore office (hybrid).
- Compensation
- Not disclosed
- Location
- Bengaluru, Karnataka, India
- Work setup
- Hybrid
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Ml / AI
- Posted
Skills
Must have
- Strong experience building backend applications with Java
- Strong experience designing, building, and operating APIs, services, and distributed systems in production
- Proficient Python skills for automation, integrations, and AI-related development
- Hands-on experience with cloud platforms (Azure, AWS, or GCP), CI/CD practices, and containerized applications using Docker
- Strong understanding of monitoring, logging, and observability
- Practical experience building, integrating, deploying, or operating AI-powered applications, LLM-based solutions, retrieval systems, or agentic frameworks professionally
Nice to have
- Experience with frameworks such as LangChain, LangGraph, CrewAI, or similar
- Familiarity with vector databases such as Pinecone, Weaviate, Milvus, Chroma, or pgvector
- Experience with RAG architectures and AI evaluation frameworks such as Ragas or Promptfoo
- Hands-on experience with Kubernetes, ideally Azure Kubernetes Service (AKS)
- Experience with Infrastructure as Code using Terraform or similar
- Experience building multi-tenant SaaS platforms or enterprise software products
Full description
Software Engineer – AI/ML
With over 20,000 customers, Crewmeister is one of the fastest-growing workforce management software providers in Germany. Our success is driven by great products, strong teamwork, and people who are passionate about building exceptional software.
As part of the ATOSS Group, we combine the agility and ownership of a scale-up with the stability and resources of a leading software company.
AI is transforming how software is built, and we're investing in engineers who can help shape that future. We believe the next generation of software development will combine strong engineering fundamentals with AI-powered workflows, tools, and product capabilities.
If you're excited about building scalable backend systems while pushing the boundaries of AI-enabled product development, we'd love to hear from you.
This role is designed for experienced software engineers whose foundation is in backend development, distributed systems, and cloud-native applications. We are looking for engineers who have already gained hands-on experience with AI-powered applications, LLMs, AI agents, or retrieval-based systems in a professional setting. However, this is not a machine learning research or AI specialist role. Your 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)
We operate in a hybrid work model with a minimum of 50% office attendance. To support onboarding, collaboration, and team integration, new team members are expected to work from our Bangalore office in Whitefield (ITPL) on a daily basis during their first six months. Following the onboarding period, the role transitions to our 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.