Staff Engineer, Agentic Developer Platform

Panorama Education is a technology company helping K-12 school systems understand what students need and take effective action. As a Staff Engineer, Agentic Developer Platform, you will design and own a new internal AI platform that will enable teams to create AI-powered workflows efficiently. This role involves making foundational architectural decisions and building the infrastructure to support various AI capabilities across the company.

Responsibilities:

• 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
• 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
• 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
• 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

Requirements:

• 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
• 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