Deutsche Telekom Digital Labs
Website:
dtdl.in
Job details:
Objective of the Role
As an Engineering Manager, you will serve as the technical and people leader for a high-performing engineering team, responsible for building scalable, intelligent, and cloud-native products. You will own the architecture, delivery, and evolution of modern microservices platforms, while also driving the adoption of AI-driven engineering practices, automation, and intelligent product capabilities.
You will work closely with product, data, and platform teams to build AI-enabled solutions, scalable backend services, and high-performance distributed systems that support evolving business and customer needs.
You Will
• Lead, coach, and mentor 3–4 Engineering Leads and a team of 25–35 engineers, fostering a culture of ownership, innovation, and continuous learning.
• Provide strong people leadership, mentoring, and communication, ensuring team growth and high performance.
• Drive technical vision, architecture decisions, and engineering excellence across backend platforms and services.
• Lead the design and development of scalable microservices-based systems using Java and cloud technologies.
• Promote adoption of AI-assisted development tools, automation, and intelligent engineering workflows to improve productivity.
• Collaborate with Product Managers, Data Scientists, AI/ML teams, QA, and DevOps engineers in an agile development environment.
• Plan, prioritize, and manage engineering deliverables across global and cross-border teams.
• Ensure best practices in code quality, observability, performance, reliability, and security.
• Drive cloud-native architecture and platform scalability using containerized and distributed systems.
• Encourage innovation by exploring Generative AI, LLM integrations, and AI-powered product features where relevant.
• Build an inclusive and high-performing culture that attracts, develops, and retains top engineering talent.
• Continuously grow as a technology leader by staying updated with modern engineering and AI trends.
You Must Have
• 11+ years of software engineering experience, preferably in a fast-paced product organization.
• 5+ years of engineering leadership experience managing large engineering teams.
• Strong experience leading backend and platform engineering teams.
• Expertise in Java ecosystem (Java, Spring Boot, REST APIs) and distributed systems architecture.
• Hands-on experience building microservices architectures, scalable APIs, and event-driven systems.
• Experience developing solutions using cloud platforms (AWS and/or Azure).
• Experience working with AI-powered systems, data platforms, or integrating ML/AI services into applications.
• Strong understanding of AI-enabled engineering tools (GitHub Copilot, AI coding assistants, automation frameworks) to improve developer productivity.
• Experience with open-source technologies and modern stack, including:
- Java / Spring Boot
- Frontend frameworks (React / Angular)
- NoSQL databases (MongoDB, Cassandra)
- Search technologies (Elasticsearch)
- Caching systems (Redis, Aerospike)
- • Experience with containerization and orchestration (Docker, Kubernetes, EKS) at scale.
- • Strong understanding of CI/CD pipelines, DevOps practices, and release strategies including:
Big Pluses If You
• Have experience building AI-driven products or integrating Generative AI capabilities into applications.
• Are comfortable collaborating across engineering, product, and data science teams.
• Have strong expertise in concurrency, multithreading, distributed systems, and high availability architectures.
• Have built systems that scale to millions of users or high transaction volumes.
• Are passionate about building products that customers love.
• Stay current with emerging technologies including Generative AI, cloud-native development, and modern architecture patterns.
• Demonstrate founder mindset, ownership, and strong problem-solving ability. 💡
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