Sr Systems Engineer

About the role

As a Sr. Systems Engineer on Uber Freight's Platform Engineering team, you'll lead the design and implementation of AI-powered developer experience tools that transform how 150+ engineering, product, and design teams work. You'll combine deep infrastructure expertise with Claude API mastery to architect autonomous workflows, intelligent dashboards, and organization-wide automation that multiplies engineering productivity. This is technical leadership for internal DevEx . You'll define standards for AI-first tooling, lead cross-functional initiatives, and mentor engineers on building production AI systems. You'll architect solutions that serve the entire CTO organization - not just write code, but establish patterns others follow. Your working style is AI-first. You default to Claude API and MCP for every automation opportunity. You think in autonomous agents, not scripts. You ship tools that learn and adapt , and you set the technical direction for how the org builds intelligent automation. What the Candidate Will Do Architect AI-Powered DevEx Systems Design and lead implementation of organization-wide DevEx platforms (like Athena: 150K JIRA issues, $35M budget tracking, CTO-wide visibility) Architect autonomous workflows - multi-agent systems for incident response, code review, deployment validation, and operational toil reduction Define MCP server standards - establish patterns for exposing internal systems (Vault, JIRA, Datadog, Jenkins) to Claude Code Lead technical initiatives - drive cross-team projects from requirements through production deployment Establish AI-first best practices - prompt engineering patterns, agent orchestration frameworks, error handling, observability for AI systems Drive Organization-Wide Impact Set technical standards for DevEx tooling across Platform Engineering, SRE, and Data Engineering teams Lead critical incident response for internal tools - advanced root cause analysis, system-wide reliability improvements Optimize organization-level systems - architect solutions that improve scalability, efficiency, and developer productivity metrics Define observability strategy for AI-powered tools - metrics, dashboards, alerts, and runbooks that ensure operational excellence Establish security and compliance frameworks - audit AI workflows, manage secrets (Vault), enforce RBAC and network policies Technical Leadership & Mentorship Mentor engineers on AI integration patterns, MCP server development, and autonomous agent design Lead code reviews for complex AI systems - ensure quality, maintainability, and adherence to standards Define and enforce operational best practices - CI/CD patterns, deployment strategies, monitoring standards Collaborate cross-functionally - work with SRE, DevOps, Data Engineering, Finance, and Product to align tooling with organizational goals Drive technical innovation - research emerging AI capabilities, prototype new approaches, evangelize successful patterns Own End-to-End Systems Architect multi-region, hybrid-cloud solutions for high-availability DevEx tools (GCP primary, OCI, Azure) Design and implement organization-level CI/CD systems integrated with AI agents for auto-remediation Lead integration projects spanning multiple teams - JIRA + GitHub + Datadog + Vault + PagerDuty data pipelines Manage infrastructure at scale - Kubernetes (GKE Autopilot), Terraform/Terragrunt, ConfigSync GitOps Ensure compliance with security standards, audit requirements, and reliability SLOs

Requirements

• Education: Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience)
• Experience: 8-12 years in platform engineering, DevOps, SRE, or infrastructure roles
• Proven AI expertise: Track record of building production systems with LLM APIs (Claude, OpenAI, etc.)
• Technical depth: Expert-level Python, Go, or TypeScript - can architect and build complex web applications and distributed systems
• Infrastructure mastery: Deep hands-on experience with Kubernetes, Terraform, multi-cloud platforms, and production operations
• Leadership: Demonstrated experience leading technical initiatives and mentoring engineers
• AI & Automation Leadership
• Claude API mastery - advanced patterns: prompt caching, extended thinking, batch processing, streaming with tool use, multi-agent orchestration
• MCP protocol expertise - built production MCP servers or contributed to MCP ecosystem; deep understanding of protocol design
• Agent framework design - architected custom agent orchestration systems, not just used off-the-shelf frameworks
• Autonomous systems - built self-healing, self-improving AI workflows that operate at production scale
• Prompt engineering excellence - published patterns, reusable templates, measurable improvements in AI system performance
• DevEx & Platform Leadership
• Organization-wide tool adopti

Additional Information

Schedule: Full Time Job Type: Hybrid Salary Type: Salary Req #: 2643

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