Software Engineer 2 - AI Transformation Engineering at Abnormal AI in Bangalore

Job description

The Opportunity Abnormal AI is the most AI-native company in cybersecurity — and we're building the internal platform that makes that real. Every function at Abnormal runs on AI-powered workflows that compound human leverage instead of replacing it. Nora is our internal AI platform, and we're investing in the engineering muscle to extend it across every record-keeping system and operational surface inside the company. We're hiring a Software Engineer II on the AI Transformation Engineering team to build that platform. If you're passionate about cutting-edge AI infrastructure, scalable systems, and shipping software that moves real business numbers, this is your opportunity. What You'll Do as a Software Engineer II As part of our Transformation Engineering team, you will: Build the Nora platform — Ship the services, factories, and sandboxes that internal teams use to deploy AI workflows. Own real platform components end-to-end. Weave AI into our internal systems — Build the connectors, services, and integrations that bring AI into the record-keeping and operational systems Abnormal already runs on (Salesforce, Jira, data warehouses, internal apps). The hard problem is making AI useful where work actually happens. Stand up net-new infrastructure — When a transformation requires capabilities that don't exist yet, you build them. Spec, ship, and harden the platform so other teams can build on top. Design for handoff — Build the platform, then transition long-term ownership to a permanent home (often a platform team in R&D). Write the docs, define SLOs, and pick the next owner before you ship. Own outcomes, not just output — Every engineer on this team owns a measurable contribution to a business outcome — revenue, cost saved, hours returned to the business, or capabilities unblocked for the teams building on top of you. Technical Requirements We're looking for engineers who have: 3+ years of professional experience in software development. Strong backend experience with Python . Fluency with the AI development stack — Claude, Codex, Gemini, Anthropic APIs, OpenAI APIs, and the surrounding tooling (APIs, MCP, agents). Bonus for building plugins, skills, or integrations against them. A track record of shipping platforms others build on — APIs, services, or SDKs that survived contact with other teams. Experience building scalable, enterprise-grade applications. Knowledge of cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Strong fundamentals in computer science, distributed systems, and performance optimization. Operator empathy — can sit with a Sales Ops or Marketing Ops lead, watch them work, and design a factory that fits the real workflow. A bias for handoff — you write docs, define SLOs, and pick the next owner before you ship. Why Abnormal AI? Build the platform that makes an AI-native company actually work — Not a demo, not a pilot. The production substrate that 2,000+ employees run on every day. Workflow ROI is the bar, even for platform work — No vanity metrics, no permanent "foundational" projects. If it doesn't move a number, we kill it or hand it off. Direct line to impact — When you ship infrastructure, Marketing, Sales, or Support starts running on it within weeks. The feedback loop is days, not quarters. Solve complex challenges at scale — Internal AI platform serving every function, built to the same standard as our customer-facing security products. Join a high-caliber team — Collaborate with industry-leading engineers, AI researchers, security experts, and operators who treat AI leverage as a first-class engineering discipline. Impact Fortune 500 enterprises — The factories you build are how Abnormal scales protection for the world's largest companies from sophisticated cyber attacks. #LI-FS1 A note on AI in our process: Abnormal AI uses AI-assisted tools to help our recruiting team prepare for candidate interviews. These tools analyze resume content and role requirements to suggest in