• You’ll become a key contributor to the team, taking responsibility for the success of some of our subsystems. • You will be participating on medium to large impact team initiatives, and within a year be able to execute on such projects. • You’ll help with interviewing potential teammates. • You’ll create technical designs that proactively address cost efficiency, security, and observability. • You’ll deliver technical plans, one-pagers, DRs, and other artifacts. • You’ll work with Kubernetes, GCP, Helm, Terraform, DataDog, ArgoCD, CircleCI, Atlantis, Docker (the list goes on) to deliver your work. • You’ll be responsible for improving developer velocity across the company (leveraging frameworks like DORA) and hardening our reliability and observability. • You’ll participate in on-call rotations and help keep all of Apollo afloat • You’ll be fully empowered to fix the root cause of issues, and ruthlessly quell any noisy monitors

Role Description Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. The Sensor Simulator Platform Team maintains the core of the simulation pipeline that allows Waymo to drive millions of simulated miles each year. The team is responsible for both the rendering/simulation engine as well as the pipeline that lets a variety of internal customers run SensorSim at scale. - Help build and maintain efficient simulators capable of running millions of simulated miles to evaluate the safety of Waymo's onboard models. - Work with multi-modal data processing and simulation, including cameras, lidar, and radar. - Interface with AI and machine learning teams that develop parts of the simulation pipeline. Qualifications - Developed or worked with 3D game engines. - Experience in approximating the real world with data simulation, which might include physics simulation, animation capture, light transport, photogrammetry, NeRFs, or Gaussian splats. - Experience in working on efficient asset management pipelines for data storage and processing. Requirements - Prior experience in working on or integrating with ML pipelines and a general understanding of how such pipelines are trained and improved. - Experience in scaling complex data processing pipelines and an understanding of the trade-offs in structuring these pipelines to operate synchronously or asynchronously. Benefits - Waymo employees are eligible to participate in Waymo’s discretionary annual bonus program. - Equity incentive plan. - Generous Company benefits program, subject to eligibility requirements. Salary Range The expected base salary range for this full-time position across US locations is: $213,000 — $263,000 USD

• Join a senior, distributed team: Become part of a closely-knit group of senior engineers at the intersection of application and infrastructure, working asynchronously with ongoing communication in public Slack channels. • Architect and build platform infrastructure: Design, build, and operate foundational components of our multi-cell platform, including service routing, cloud networking, and the control plane for managing account lifecycles. • Drive seamless migrations: Develop and automate the tooling to migrate customer accounts from legacy environments to the new multi-cell architecture at scale. • Develop scalable backend services: Write robust, high-quality backend services and infrastructure code, primarily in Go and Python, with opportunities to work with Rust. • Tackle cloud networking challenges: Collaborate on network architecture design, including VPC management, load balancing, DNS, PrivateLink, and service mesh configurations to support single-tenant and multi-tenant deployments. • Automate for scale: Design and implement automation using tools like Argo Workflows, Kubernetes, and Terraform to enhance the reliability, efficiency, and scalability of our platform. • Collaborate and mentor: Work closely with product engineering teams, security, and customer support to unblock feature conformance, define technical direction, and mentor other engineers. • Own and troubleshoot: Take strong ownership of distributed systems, troubleshoot complex issues across application and network layers, and participate in an on-call rotation to maintain high availability.

Role Description Panorama is at an inflection point with AI - we've heavily invested in it across our products and seen incredible market traction and now we're turning towards how we can use AI to transform how the company itself operates. As a Staff Engineer, Agentic Developer Platform, you'll design and own a new internal AI platform: the agent framework, skill infrastructure, and shared systems that every team at Panorama builds on. The goal is making it possible for engineers, PMs, and operators across the company to go from idea to working AI-powered workflow through core infrastructure. The work is greenfield. You'll make early architectural decisions that others will build on, create the tooling that turns experiments into things teams can actually rely on, and stay close enough to how people use what you build to keep improving it. This role is for someone who thinks in platforms, gets energy from enabling others, and wants what they build to matter, both inside the company and for the 15 million students we serve. What You'll Do: - Platform Architecture & AI Infrastructure - Design and own the company's core AI infrastructure: the shared systems, integration patterns, and runtime environments that all AI-powered work is built on top of. - Make the foundational decisions that others will depend on, including model selection and abstraction, orchestration patterns, data access layers, and deployment standards. - Design the platform so teams can extend it on their own, without needing your involvement for every new use case. - Build the operational layer teams need to trust what they've deployed: logging, evals, cost tracking, latency monitoring, and feedback loops. - Agent & Skill Framework - Design and build the company's agent framework and skill library, the reusable building blocks that teams reach for when automating workflows, connecting systems, or extending AI capabilities into new areas. - Define the interfaces, contracts, and composition patterns that let squads build new agents and skills confidently without reinventing core infrastructure. - Ensure the framework supports a range of complexities, from simple single-step automations to multi-agent workflows spanning systems and teams. - Adoption and Partnership - Help internal teams go from "we have an idea" to "we have a working implementation" by providing the technical scaffolding, guidance, and support. - Build the internal tooling, documentation, and onboarding paths that make the platform genuinely accessible to team members across the company. - Create abstractions that lower the floor for AI development without boxing in the complex cases. - Act as a technical partner to teams adopting the platform, helping them get unblocked, apply patterns correctly, and avoid pitfalls early. - Partner with Product to surface where AI capabilities can remove friction, accelerate workflows, or unlock things internal teams don't yet know are possible. - Maintain a feedback loop with internal customers so the platform evolves around how people actually work, not how the roadmap assumed they would. - Standards, Governance & Technical Direction - Define how the company evaluates, adopts, and evolves AI capabilities responsibly, establishing standards for safety, reliability, and quality that hold across teams. - Partner with engineering leadership to align AI infrastructure with broader architectural direction and long-term system health. - Contribute to org-wide technical discussions, bringing a platform and infrastructure lens to decisions that affect how AI work gets done across the company. Qualifications - 8+ years of professional software engineering experience, with meaningful depth in platform, infrastructure, or developer tooling. - Experience building shared systems that other engineers build on, and an intuition for what makes internal platforms succeed or stall. - Hands-on experience with production AI systems (LLM integrations, tool-using agents, retrieval pipelines, or comparable work), and a track record of enabling other builders to work with those systems confidently. - Strong instincts for API and abstraction design, knowing how to expose the right surface area and hide the right complexity. - Familiarity with MCP or similar tool-use and integration patterns. - A track record of scoping and delivering greenfield technical work, including making early architectural decisions that hold up over time. - Collaborative and transparent by default, with the ability to lead cross-functional alignment without formal authority. - Clear-eyed about the gap between AI that works in demos and AI that works in production, and experienced in closing it. - Actively seeks out product and cross-functional context, energized by the opportunity to push the work forward across teams, not just within engineering. Nice to Have: - Experience with multi-agent orchestration frameworks. - Background in internal developer platforms, enablement engineering, or technical program leadership. - Experience in defining and rolling out engineering standards across a multi-team organization. Benefits - Base Salary: The base salary range for this position is $233,750 - $343,750 // Annually. - 401K with an employer match. - Health, dental, vision, life insurance, and short-term and long-term disability coverage. - Flexible spending account for health care and dependent care. - Wellness Reimbursement. - Work from Home Reimbursement. - Flexible vacation policy. - Parental leave program. - Company Issued Laptop.