Senior Software Engineer, Lifecycle
New
Based in United StatesFull-TimeSenior
SalaryCompetitive compensation including base salary, bonus opportunities, and equity grants
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Job Details
- Experience
- 4+ years of experience in software engineering
- Required Skills
- AWSPythonJavaKotlinRubyRESTful APIsMicroservicesDistributed Systems
Requirements
- 4+ years of experience in software engineering, ideally in backend or distributed systems roles within SaaS, growth, or platform teams.
- Strong proficiency in at least one backend language such as Java, Kotlin, Python, or Ruby.
- Experience building APIs and microservices in cloud environments (preferably AWS).
- Experience working with event-driven architectures, streaming systems, or real-time messaging infrastructure.
- Familiarity with lifecycle marketing systems, CDPs, segmentation, or customer engagement platforms is highly desirable.
- Ability to work with large-scale datasets through APIs, pipelines, or reverse ETL-style systems.
- Strong problem-solving skills with the ability to independently drive projects in ambiguous, fast-paced environments.
- Excellent communication skills, with the ability to collaborate effectively across distributed, cross-functional teams.
- Strong ownership mindset and attention to system reliability, scalability, and long-term maintainability.
Responsibilities
- Design and build scalable backend services and APIs that power unified lifecycle communications across SMS, email, push, and future channels.
- Develop real-time, event-driven messaging systems and automation capabilities that support personalized customer engagement and experimentation.
- Translate complex behavioral and product data into actionable lifecycle workflows using APIs, streaming systems, and data pipelines.
- Partner closely with product managers, lifecycle marketing, data, analytics, and ML teams to define requirements and deliver high-impact solutions.
- Own medium-scale projects end-to-end, from design through deployment, managing ambiguity and technical trade-offs along the way.
- Improve system reliability, scalability, and performance while ensuring clean architecture and maintainable codebases.
- Contribute to engineering best practices by enhancing observability, documentation, and cross-functional communication around system behavior.
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