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Full-stack Engineering Team Lead
Не указаноПолная занятостьFull-stack DevelopmentDefense and Space Manufacturing
Lead and mentor a team responsible for designing, developing, and operating scalable, distributed, data-intensive cloud systems. The role combines people leadership, architecture, hands-on software development, and operational ownership.
Обязанности
- Lead, mentor, and develop a full-stack engineering team
- Own systems end to end, from architecture and development through production operations and continuous improvement
- Lead the design and development of scalable, distributed, data-intensive systems
- Make architectural decisions involving scalability, performance, availability, reliability, and maintainability
- Contribute hands-on to frontend, backend, data, and infrastructure development
- Lead effective and responsible adoption of AI-assisted development tools
- Establish engineering standards for code quality, testing, security, observability, and operational readiness
- Collaborate with Product, DevOps, and Systems Engineering on planning, prioritization, and delivery
Требования
- At least 7 years of professional software engineering experience, including significant backend experience
- At least 3 years of technical team leadership experience
- Bachelor’s degree in computer science, software engineering, or a related technical field
- Strong experience with JavaScript, TypeScript, React, Node.js, and REST API design
- Production experience with Docker and Kubernetes
- Experience with AWS or an equivalent cloud environment
- Experience with large-scale, high-throughput, or highly available production systems
- Strong system design and architectural decision-making skills
- Hands-on use of AI-assisted development tools in daily engineering work
- Experience with multiple databases, such as PostgreSQL, MongoDB, Cassandra, Redis, or Elasticsearch
- Experience with Kafka or event streaming, microservices, or event-driven architectures
Будет плюсом
- Python development experience
- Experience integrating AI or large language model services into products or internal tools