Role overview

Senior Software Engineer II, FAI

Requirements and responsibilities

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About the Job

  • Design, build, and operate resilient, low-latency microservices and data pipelines that power fulfillment planning, inventory availability, and delivery promises.
  • Partner with machine learning and data science to productionize models and features, enable online experimentation, and continuously improve decision quality.
  • Own services end-to-end, from technical design and RFCs through implementation, rollout, observability, and participation in an on-call rotation.
  • Drive reliability, scalability, and cost efficiency through SLOs, capacity planning, incident reviews, and performance optimization.
  • Collaborate cross-functionally with Product, Marketplace, and Operations to define roadmaps and deliver measurable customer and business impact.
  • Mentor other engineers via code and design reviews, pair programming, and contributions to engineering best practices and standards.

Minimum Qualifications

  • 6+ years of professional software engineering experience building backend services or distributed systems.
  • Proficiency in at least one of the following languages: Go, Java, Python, or Scala.
  • Hands-on experience designing and operating microservices on a major cloud provider (AWS, GCP, or Azure) using containers/orchestration (Docker, Kubernetes).
  • Strong SQL skills and experience with event streaming and data stores (e.g., Kafka or Pub/Sub; Redis; PostgreSQL or MySQL).
  • Proven ownership of production services, including observability (metrics, logging, tracing) and participation in an on-call rotation.
  • Experience delivering in an agile environment and collaborating effectively with product managers, data scientists, and cross-functional partners.
  • Bachelor’s degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience.

Preferred Qualifications

  • Experience building real-time decisioning systems for logistics, marketplaces, ads, or e-commerce.
  • Familiarity with ML feature stores, model serving, or experimentation platforms and A/B testing frameworks.
  • Knowledge of algorithms and data structures relevant to optimization problems (e.g., routing, matching, forecasting).
  • Experience with the GCP ecosystem (e.g., GKE, Pub/Sub, BigQuery, Cloud SQL) or equivalent services on other clouds.
  • Demonstrated impact mentoring engineers and leading cross-team technical initiatives from concept to production.
  • Comfort operating in fast-paced, ambiguous environments and iterating quickly based on data and user feedback.
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Browse stack
FocusSoftware EngineeringRole area
Seniority signalSeniorCandidate level
StackAWS, Azure, DockerPrimary skills
Location1 accepted countryEligibility

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