Software Development Engineer, Benefits Experience & Technology (BXT)

DESCRIPTION

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 is a generative-AI and agentic-engineering role first, building products that reach millions of people.

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. When a parent opens the app at 6 a.m. with a feverish child, they get a confirmed appointment and a real price in under two minutes. It is built on secure, HIPAA-compliant foundations to serve very large member populations.

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.

This role places you on one of these two teams.

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. You write the specification and set the acceptance criteria; agents write a growing share of the implementation, author tests, and resolve code-review comments; you direct, validate, and own what ships. You will still write code by hand when the problem is novel, the domain is opaque to current models, or the systems and security boundaries demand it, and that balance shifts toward direction as our tooling matures. 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.

How we work, honestly: teams here are small, which means high ownership density and real scope decisions rather than a ticket queue. Some of our work carries hard, externally committed launch dates, so parts of this role are deadline-driven. Because we handle sensitive personal data, privacy and security are designed in from the start and are everyone’s responsibility, not an afterthought. You own what you build, including its operations and an on-call rotation. In return you build rare, portable depth: regulated, large-scale platforms and production agentic systems, plus the judgment to direct them.

This role is for builders who want to own outcomes, not tickets, and who are comfortable working on systems that do not fully exist yet. If greenfield 0-to-1 problems energize you, if you want to help prove how a small team enters a hard domain and wins, and if you see AI as the leverage that lets a handful of engineers build what used to take dozens, you will thrive here.

Key job responsibilities

Own capabilities end to end: design, build, test, launch, and operate features and independently deployable services, including on-call for what you ship.

Work backwards from the customer: bring a product design perspective to what you build, understanding the need behind the spec and shaping the experience, not just implementing it.

Turn signed-off specifications into working, tested software, contributing across packages in our open-contribution model and partnering with product experts to refine requirements.

Work the AI Native build loop day to day: direct coding agents, review human-authored and agent-authored code to the same bar, and own the correctness of what merges.

Implement and extend the validation that earns autonomy: simulation tests across realistic customer segments, so a change is proven correct across the populations we serve before a human reviews it.

Integrate with regulated, real-world systems (sensitive customer data, third-party and vendor APIs) with correctness and privacy as non-negotiables.

Help improve the system that builds the system: when a manual fix reveals a pattern, propose it as a reusable skill in our shared capabilities so agents handle it next time.

BASIC QUALIFICATIONS

3+ years of non-internship professional software development experience

2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience

1+ years of software development engineer or related occupational experience

1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience

1+ years of Object Oriented Design experience

Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field

Experience programming with at least one software programming language

PREFERRED QUALIFICATIONS

3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience

Bachelor's degree in computer science or equivalent

Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience building complex software systems that have been successfully delivered to customers

Experience implementing AWS services in a variety of distributed computing environments

Exposure to the broader agentic ecosystem and open-source AI or agent tooling

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, TX, Dallas - 143,700.00 - 194,400.00 USD annually