Requirements

Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field, or equivalent practical experience
4+ years of professional software engineering experience building backend services and distributed systems
Proficiency in one or more of Go, Java, or Python; ability to write efficient, maintainable, well‑tested code
Hands‑on experience designing and operating service APIs (REST/gRPC/GraphQL) and event‑driven systems (e.g., Kafka, Pub/Sub, SQS)
Solid understanding of distributed systems concepts: consistency models, idempotency, transactions/atomicity, retries/backoff, and failure isolation

Nice to Haves

Experience integrating with enterprise SaaS (e.g., Salesforce, Workday, ServiceNow, Okta) and identity protocols (OAuth2/OIDC/SAML, SCIM); familiarity with webhook security and lifecycle
Cloud proficiency (AWS/GCP/Azure), serverless (Lambda/Cloud Functions), and infrastructure as code (Terraform); secrets and key management (KMS/Vault)
Security & compliance awareness: IAM, SSO/MFA, audit logging, data classification/PII handling, and privacy considerations (e.g., GDPR/CCPA)
Demonstrated use of AI tools across the SDLC (code generation, test scaffolding, runbook/RFC drafting) to improve developer productivity
Experience mentoring junior engineers, conducting design reviews, and authoring clear technical documents/RFCs

Drive observability end‑to‑end: metrics, logs, traces, SLOs/error budgets, alerting, and playbooks; participate in on‑call and lead incident/root‑cause analysis
Partner with Security, Data, and Application teams to ensure integrations meet security, privacy, and compliance requirements (authn/z, data governance, auditability)
Improve reliability and efficiency through automation (testing, deployments, backfills, data repair tools) and infrastructure improvements (Kubernetes, IaC)
Profile and optimize service latency, throughput, and cost; plan capacity and scaling strategies for peak workloads and partner/third‑party limits
Author and review technical designs/RFCs, make pragmatic trade‑offs, and align stakeholders on solutions to ambiguous integration problems
Mentor peers through code/design reviews and knowledge sharing; raise the bar on engineering quality, monitoring, and operational excellence
Leverage AI where it measurably helps (test generation, code/infra scaffolding, diagnostics, documentation) and instrument results to demonstrate impact

Opportunity to work on impactful projects that shape the daily experience of tens of thousands of employees
Be part of a lean and fast-moving team focused on driving real productivity gains and meaningful business impact
Potential accommodations available based on religious and/or medical conditions, or as required by applicable law
Collaborative office environment central to Uber's cultural identity