Senior Software Engineer - App Foundations

About the Role

Abnormal AI is looking for a Senior Backend Engineer to join the App Foundations team. App Foundations owns the core customer-centric data and platform services that every Abnormal product depends on — our MPP API and customer data model, the Notifications Platform, License Entitlement, Package Management, Large Model Service (LMS, our internal LLM inference platform), and the MPP Go Service that sits behind our Portal. If a product at Abnormal is launching, scaling, or talking to a customer, it’s almost certainly running on something we own.

This is a senior IC role for a generalist backend engineer who wants to own systems end-to-end, raise the technical and operational bar, and help shape how a platform team operates in an AI-native company. You’ll rotate across our surfaces rather than specializing in one — which means your first year spans API design, distributed systems reliability, LLM inference infrastructure, and the kind of hard, cross-team platform work that determines whether new products ship cleanly.

The ideal candidate is a product-minded, principle-first engineer who takes extreme ownership, communicates crisply, and treats AI tools as a core part of how they build — not a side experiment.

What you will do

• 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,