Sr. Software Dev Engineer, Benefits Experience and Technology (BXT)

About the role

Using your benefits today means portals, phone calls, hold music, and fine print. We are changing that by bringing AI in as a strategic partner: software that understands what a person needs and helps them find the answer at the moment of need. This posting is for the tech lead on one of our two biggest product bets, driving large, ambiguous problems that span multiple organizations. This is a generative-AI and agentic-engineering role first, at very large scale.

You will join Benefits Engagement Technology and Services (BETS), the Amazon organization reinventing how more than a million employees and their families engage with their benefits. Our vision is benefits that are AI-powered, personalized, and proactive, where timely guidance reaches people when they need it rather than making them hunt for it. BETS builds and operates the platform that delivers benefits experiences across mobile, web, and an AI assistant, from self-service content creation to multi-channel campaigns to analytics, and we are now building a family of AI-native products on top of it.

Two of those products are our biggest bets, and we are building each as a focused product team inside BETS:

- A reimagined health plan where AI is a strategic partner for members instead of a portal to navigate. Rather than directories, phone trees, and hold music, it understands what someone needs and brings the right answer to them at the moment of need: the in-network doctor, the real out-of-pocket cost before they book, the claim explained in plain language, and the next step taken on their behalf. It is built on secure, HIPAA-compliant foundations to serve very large member populations, with a path to serve other organizations over time.

- An agentic workforce for benefits operations that makes running benefits for a workforce of millions dramatically easier. Managing dozens of programs, vendors, and budgets is enormous operational work; AI agents take on that heavy lifting, surfacing what needs attention, preparing the analysis and the recommended action, and handling the routine, so the people who manage benefits spend their time on decisions and strategy instead of manual operations. The system learns from every decision and keeps that knowledge with the team.

You will be the tech lead on one of these two products.

Here is what sets this organization apart: we do not just build AI products, we build them the AI Native way, and we have already proven it. A small pod rebuilt a major benefits platform and shipped it to production in 3 months, work originally scoped at 12, by restructuring how we engineer around agents. In our model, humans own judgment and agents own the mechanical middle. Engineers write the specification and set the acceptance criteria; agents (Claude Code, Kiro) write a growing share of the implementation, author tests, and resolve code-review comments; engineers direct, validate, and own what ships, and still hand-write the novel, ambiguous, and infrastructure-heavy work where models fall short. Recursive self-improvement, where the system proposes its own next version and a human approves, is the north star we are deliberately climbing toward, one validated step at a time, with humans at the judgment gates.