Software Engineer II

About the Role

At Uber, the Digital Experience (DE) team is reimagining how employees interact with internal systems. We combine solid software engineering with smart, AI-driven product thinking to build tools and automations that make work smoother, faster, and more efficient. From day one, DEE has focused on driving real productivity gains and meaningful business impact.

1. As a Software Engineer on this lean and fast-moving team, you'll be building scalable backend systems that turn slow, manual processes into smart, automated workflows. You'll help reduce repetitive operational work and improve support across enterprise functions like HR, IT, and Security. It's hands-on, impactful work that makes a difference every day.
2. You'll work closely with internal teams and SaaS platforms, using technologies like Java, Go, Python, and Generative AI (GenAI). Whether you're optimizing a process that used to take hours or building an AI assistant to handle support tickets, your work will directly shape the daily experience of tens of thousands of Uber employees, helping us move faster, stay focused, and get more done with less.
3. If you're excited by the idea of building intelligent systems that empower people and drive change at scale, we'd love to have you on board.

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

1. Bachelor's degree in Computer Science, Engineering, Mathematics, or related field, or equivalent practical experience.
2. 4+ years of professional software engineering experience building backend services and distributed systems.
3. Proficiency in one or more of Go, Java, or Python; ability to write efficient, maintainable, well-tested code.
4. Hands-on experience designing and operating service APIs (REST/gRPC/GraphQL) and event-driven systems (e.g., Kafka, Pub/Sub, SQS).
5. Solid understanding of distributed systems concepts: consistency models, idempotency, transactions/atomicity, retries/backoff, and failure isolation.

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