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Manager, Software Development ( Java & AWS )

Infor
Hyderabad, IND
Full-time
Senior · 12–15 years experience
Hybrid
Discovered 3 weeks ago
JavaSpring BootAWSKubernetesKafkaSQL

Full Job Posting

A Typical Day in the Life Includes:

Lead and develop engineering teams, including hiring, mentoring, and performance management

Own end-to-end delivery of platform features from design through production support

Define and drive technical architecture in collaboration with architects and senior engineers

Ensure platform scalability, reliability, and performance in production environments

Establish and enforce engineering best practices, including code quality, testing, and CI/CD

Collaborate with product management to translate business requirements into technical solutions

Drive operational excellence, including monitoring, incident management, and continuous improvement

Ensure systems meet security, compliance, and data protection requirements

Manage priorities, timelines, and stakeholder expectations for platform delivery

Foster a culture of accountability, innovation, and continuous learning within the team

Basic Qualifications:

  • 12–15 years of total experience in software engineering
  • 3–5 years of experience in engineering management or technical leadership roles
  • Proven experience building and operating cloud-native SaaS platforms at scale
  • Experience working in enterprise product organizations with distributed systems
  • Deep expertise in Java, Spring Boot, and backend service development
  • Strong understanding of distributed systems, microservices, and event-driven architectures
  • Experience with cloud platforms, preferably AWS
  • Proficiency with Kubernetes, containerization, and cloud-native deployment models
  • Strong knowledge of data storage technologies (SQL/NoSQL) and data modeling
  • Familiarity with document management or content management systems
  • Understanding of API design, system integration, and data workflows
  • Experience with messaging/streaming platforms (e.g., Kafka or equivalent)
  • Understanding of observability tools (logging, metrics, tracing) and SRE practices
  • Knowledge of software development lifecycle (SDLC) and DevOps practices
  • Awareness of AI/ML applications in enterprise systems is a plus
  • Strong problem-solving and decision-making skills
  • Effective communication and stakeholder management skills

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