About Deutsche Telekom Services Europe Romania
In Romania, Deutsche Telekom has set up a Shared Service Center in Bucharest & Timisoara - Deutsche Telekom Services Europe Romania (DTSE Romania), which delivers support function services such as HR, Accounting, Reporting and Finance, as well as IT support services for these lines of business, for the whole European Deutsche Telekom footprint since July 2013.
We are focused on:
- the best customer experiences
- delivering high quality services
- great working conditions
- growing with innovations
- continuously improving competitiveness through digitalization
You should bring strong backend engineering experience, a pragmatic mindset, and the ability to communicate technical topics clearly to both technical and non-technical audiences. Beyond technical implementation, we are looking for someone who thinks like an IT consultant: someone who understands stakeholder needs, asks the right questions, challenges assumptions constructively, and helps identify the best possible solution for the given business and technical context.
Key responsibilities:
- 5+ years of professional software engineering experience, with a strong focus on backend development and Python for production grade systems
- Solid experience building backend services, APIs, and distributed systems
- Experience with containers and deployment technologies such as Docker, Kubernetes, or serverless platforms
- Good understanding of software architecture, clean code principles, and engineering best practices
- Experience working with Git, pull requests, code reviews, and collaborative development workflows
- Practical experience with CI/CD and GitOps concepts and tools
- Ability to work independently, take ownership, and drive topics forward
- Strong communication skills and the ability to explain technical concepts in clear, simple, and stakeholder-appropriate language
- An outgoing, collaborative personality and a genuine interest in working with colleagues to find good solutions
- Designing and implementing production-grade backend services, APIs, and integration components for data- and AI-enabled applications
- Translating business requirements into technical concepts and scalable, secure, maintainable software architectures while driving their implementation within small, cross-functional teams
- Building production-grade agentic workflows on an existing agentic workflow platform and integrating them with enterprise systems, APIs, data sources, knowledge bases, and business processes
- Ensuring the reliable and controlled operation of AI applications through automated testing, error handling, fallbacks, guardrails, human-in-the-loop mechanisms, security, observability, traceability, and auditability
- Developing solutions iteratively from PoC and prototype stages to production, including deployment, go-live support, troubleshooting, and technical stabilization
- Establishing engineering practices such as code reviews, CI/CD, GitOps, automated integration and end-to-end testing, and technical documentation
- Ensuring a structured handover to MLOps or operations teams, including deployment procedures, monitoring, runbooks, operational documentation, and knowledge transfer
- Collaborating with product owners, architects, data scientists, MLOps engineers, security specialists, platform teams, and business stakeholders to evaluate solution options, explain trade-offs, and identify technical risks and dependencies
- Contributing reusable components, integration patterns, and engineering standards while supporting other engineers through technical guidance, mentoring, and code reviews
Nice to have:
- Knowledge of data engineering concepts, such as ETL/ELT pipelines, data transformation, batch processing, data quality, or orchestration tools
- Experience with deployments on hyperscaler platforms such as AWS, Azure, or Google Cloud Platform
- Experience with AI-enabled backend applications, especially RAG-based systems, semantic search, document Q&A, internal knowledge assistants, or agentic workflows using tools such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, OpenAI, Azure OpenAI, Anthropic, or similar technologies
- Familiarity with typical RAG stack components, such as embeddings, chunking, vector databases/search engines like pgvector, Pinecone, Weaviate, Qdrant, OpenSearch, Elasticsearch, or Azure AI Search, as well as observability/evaluation tools such as LangSmith, Langfuse, OpenTelemetry, or Arize Phoenix
- Experience with monitoring, logging, tracing, and observability tools
- Full-stack capabilities and experience in building frontends are a big plus
- Familiarity with security, authentication, authorization, and secure API design
- Experience mentoring engineers or leading technical initiatives
DTSE-RO is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. All employment decision at DTSE-RO are based on business needs, job requirements and individual qualifications, with no regard to race, color, religion or belief, national, social or ethnic origin, sex, age, physical, mental or sensory disability, sexual orientation and gender identity.
DTSE-RO will not tolerate discrimination or harassment based on any of these characteristics.
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