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Protocol Intelligence
Data-driven signals on your job's competitivenessStrong employer brand, Bangalore metro location, and broad engineering-manager scope raise candidate competition.
Requires deep systems, reliability, and logistics integrations, moderately limiting cross-industry transferability.
Explicit 7+ years, 1–3 years management, and mandatory systems and operations experience increase shortlisting strictness.
Job Description
Structured overview of role & requirementsAbout This Role
Lead and develop high-performing engineering teams responsible for business-critical transportation systems spanning carrier scheduling, delivery, yard operations, shipping documentation, and system integrations.
Own engineering strategy, product delivery, technical health, and operational excellence including reliability, security, scalability, and observability of distributed, event-driven systems and APIs.
Manage complex technical strategy and modernization efforts, operational discipline, and external technology partnerships ensuring measurable business and operational outcomes.
Minimum Requirements
4-year degree or equivalent experience.
7+ years engineering/software development experience, including building and operating distributed enterprise applications in production.
1-3 years engineering management experience with demonstrated ability to develop engineers and deliver cross-functional products or platforms.
Strong experience in production operations, reliability engineering, and managing resilient APIs, microservices, event-driven architectures, and complex system integrations.
Ideal Candidate Profile
Experienced leader combining deep technical knowledge of modern application development, event streaming, cloud infrastructure, CI/CD, automated testing, secure software development, and DevOps.
Proven ability to balance architecture modernization, technical debt management, and delivery priorities across complex enterprise ecosystems.
Skilled at managing external technology partners, cross-team dependencies, and fostering engineering teams capable of operational excellence and adopting AI-assisted engineering practices.