Design, build, and operate high-performance, low-latency services across the App Foundations portfolio — Python/Django, Go, MySQL/PostgreSQL, Kafka, Redis, and ElasticSearch — in close partnership with engineers, designers, PMs, and EMs across R&D. - Lead end-to-end delivery of platform features and stability workstreams — from tech design and PRR through launch, post-launch ops, and long-term ownership. - Raise the operational bar: drive SLO-backed reliability work on Tier-0 systems like Notifications and LMS, improve our observability and on-call posture, and reduce unplanned work on the systems you own. - Contribute to our LLM inference platform (LMS) — model routing and fallback, provider integrations (Azure OpenAI, Bedrock), batch/async inference, cost attribution, and the safety rails that let product teams ship AI features without reinventing the stack. - Build AI-native internal tools that change how the team operates: automated ticket triage, on-call copilots, post-mortem drafting, customer-request classifiers — following the precedent of our Nora workflow and existing Claude skills. - Mentor other engineers, drive tech design and PR reviews, and be a credible SME for the systems you own. - Partner with product managers, TPMs, and peer platform teams (Portal, Customer Journey, Data Security, FedRAMP) to land complex cross-team initiatives cleanly. - Participate in hiring: write questions, run loops, and help bring the next wave of AF engineers on board. ##
AI-Forward Hiring
App Foundations is an AI-native team. We expect every engineer — from Day 1 — to use AI coding tools (Cursor, Claude Code, and the rest) as the default way they write and review code, and to design AI leverage into the workflows they own. This role is explicitly for someone who already operates this way and wants to push it further. In interviews, we’ll look for concrete evidence that you:
Use AI tools daily to ship faster — and can talk specifically about where they help, where they hurt, and how you’ve adjusted your workflow. - Have built or shipped something AI-powered beyond the IDE — a script, an agent, a workflow automation, a production feature — that actually changed how work got done. - Think at the workflow level, not just the keystroke level: you look at an ops process, a support queue, or a team ritual and ask “what should an agent own here?”
Have opinions about how AI changes the role of a senior engineer in the next 1–3 years, and are excited about a team that treats AI as core infrastructure rather than an experiment. Because we own LMS, experience building with LLMs in production — provider APIs, evals, model routing, cost and quota management — is a strong plus, but not required. ## Must Have Skills
5+ years of backend software engineering experience building and operating production services at scale. - 4+ years on relevant tech stacks — Python (Django) and/or Go; MySQL / PostgreSQL; and hands-on experience with Kafka, Redis, and ElasticSearch. - 3+ years supporting enterprise-class customers in production, including ownership of SLOs, on-call, and incident response. - 2+ years of system design experience — demonstrated ability to design, document, and land non-trivial cross-team architectures. - Proven experience leading multi-quarter projects end-to-end: tech design, implementation, launch, and post-launch operations. - Demonstrated daily use of AI coding tools in your current workflow, and specific examples of where you’ve used AI to improve how you or your team works beyond just code generation. - Strong written and verbal communication; proven ability to collaborate autonomously and asynchronously with remote stakeholders. - Bachelor’s degree in Computer Science or equivalent professional experience. ## Nice to Have
Hands-on experience building with LLMs in production — provider APIs (OpenAI/Anthropic/Bedrock), model routing and fallback, evals, batch inference, or cost/quota tooling. - Experience with notification delivery systems, licensing/entitlement platforms, or other high-leverage internal platforms used by many product teams. - Experience building and shipping AI agents or automations (coding agents, ops agents, classifier pipelines) that replaced meaningful manual work. - Experience mentoring engineers and acting as a tech lead on at least a small squad. - Master’s degree in Computer Science or a related field. #LI-AJ1
Actual compensation will be determined based on several non-discriminatory factors including skills, experience, qualifications, and geographic location. In addition to base salary, this role may be eligible for bonus or incentive compensation, equity, and a comprehensive benefits package. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.
