Software Development Engineer II, FBA
Amazon•Published 1 days ago•First seen 22 hours ago
Software Development Engineer II — AI-Native Engineering Systems, FBA
WANT TO BUILD AI SYSTEMS — NOT CARRY A PAGER?
Fulfillment by Amazon (FBA) lets sellers worldwide leverage Amazon's world-class logistics infrastructure — storage, fulfillment, delivery, returns — as a service. Sellers from Fortune 50 companies to hundreds of thousands of small businesses in 135+ countries rely on FBA, which powers tens of billions in annual GMS across dozens of categories.
Most engineering teams spend their best hours reacting — triaging tickets, babysitting deployments, answering the same operational questions over and over. We're building the opposite team. Our entire charter is to build the AI-native systems that make reactive work disappear: agents that resolve operational issues before a human sees them, self-healing pipelines that deploy without manual gates, and a knowledge foundation that lets software answer for itself. You won't be absorbing FBA's operational load — you'll be engineering it out of existence.
This is a VP-funded, multi-year charter with end-to-end ownership and a leadership-backed mandate. You'll work at the frontier of applied AI — LLM-powered remediation agents, machine-readable operational knowledge, autonomous deployment systems — and see your work adopted across 55+ teams and 500+ engineers. We operate with startup intensity inside Amazon: small teams, fast cycles, and the freedom to invent.
Why this team is different
Build systems, not backlog. Your job is to invent AI-native tooling — not to sit in an operational queue. Your work is measured by how much reactive toil it eliminates for other teams.
AI at the core, not bolted on. You'll ship LLM-powered remediation agents, autonomous workflows, and a knowledge foundation that makes AI-assisted development the default across FBA — real production systems, not prototypes.
Learn from the best. You'll join a dedicated pod with direct access to multiple senior and Principal SDEs for design guidance, code review, and mentorship — with a clear path to grow your scope and visibility on a VP-sponsored charter.
Provable impact. Your systems free up the equivalent of dozens of engineers across FBA — measured, visible, and tied directly to a leadership-backed goal.
What you'll build
Agentic remediation systems — LLM-powered agents that detect, diagnose, and resolve operational issues automatically, replacing manual runbooks with self-executing guidance.
Self-healing deployment platforms — safe primitives, automated integration testing, and pipeline intelligence that drive teams toward fully continuous, hands-off delivery.
The FBA knowledge foundation — the OE infrastructure and knowledge-graph tooling that let AI systems reason about FBA's services and answer operational questions autonomously.
Basic qualifications
3+ years of non-internship professional software development experience
Experience programming with at least one modern language (Java, C++, Python, etc.)
Experience contributing to the architecture and design (design patterns, reliability, scaling) of new and current systems
Experience with the full software development lifecycle — coding standards, code reviews, source control, build processes, testing, and operations
Preferred qualifications
Experience building automation, platform, or developer-productivity systems (CI/CD, observability, agentic/AI-assisted tooling)
Hands-on interest in applying LLMs and AI-native approaches to real engineering problems
Familiarity with continuous delivery and autonomous deployment practices
Bias for measurable impact and comfort inventing in an ambiguous, high-ownership charter
Key job responsibilities
Software Development Engineer II — AI-Native Engineering Systems, FBA
WANT TO BUILD AI SYSTEMS — NOT CARRY A PAGER?
Fulfillment by Amazon (FBA) lets sellers worldwide leverage Amazon's world-class logistics infrastructure — storage, fulfillment, delivery, returns — as a service. Sellers from Fortune 50 companies to hundreds of thousands of small businesses in 135+ countries rely on FBA, which powers tens of billions in annual GMS across dozens of categories.
Most engineering teams spend their best hours reacting — triaging tickets, babysitting deployments, answering the same operational questions over and over. We're building the opposite team. Our entire charter is to build the AI-native systems that make reactive work disappear: agents that resolve operational issues before a human sees them, self-healing pipelines that deploy without manual gates, and a knowledge foundation that lets software answer for itself. You won't be absorbing FBA's operational load — you'll be engineering it out of existence.
This is a VP-funded, multi-year charter with end-to-end ownership and a leadership-backed mandate. You'll work at the frontier of applied AI — LLM-powered remediation agents, machine-readable operational knowledge, autonomous deployment systems — and see your work adopted across 55+ teams and 500+ engineers. We operate with startup intensity inside Amazon: small teams, fast cycles, and the freedom to invent.
Why this team is different
Build systems, not backlog. Your job is to invent AI-native tooling — not to sit in an operational queue. Your work is measured by how much reactive toil it eliminates for other teams.
AI at the core, not bolted on. You'll ship LLM-powered remediation agents, autonomous workflows, and a knowledge foundation that makes AI-assisted development the default across FBA — real production systems, not prototypes.
Learn from the best. You'll join a dedicated pod with direct access to multiple senior and Principal SDEs for design guidance, code review, and mentorship — with a clear path to grow your scope and visibility on a VP-sponsored charter.
Provable impact. Your systems free up the equivalent of dozens of engineers across FBA — measured, visible, and tied directly to a leadership-backed goal.
What you'll build
Agentic remediation systems — LLM-powered agents that detect, diagnose, and resolve operational issues automatically, replacing manual runbooks with self-executing guidance.
Self-healing deployment platforms — safe primitives, automated integration testing, and pipeline intelligence that drive teams toward fully continuous, hands-off delivery.
The FBA knowledge foundation — the OE infrastructure and knowledge-graph tooling that let AI systems reason about FBA's services and answer operational questions autonomously.
Basic qualifications
3+ years of non-internship professional software development experience
Experience programming with at least one modern language (Java, C++, Python, etc.)
Experience contributing to the architecture and design (design patterns, reliability, scaling) of new and current systems
Experience with the full software development lifecycle — coding standards, code reviews, source control, build processes, testing, and operations
Preferred qualifications
Experience building automation, platform, or developer-productivity systems (CI/CD, observability, agentic/AI-assisted tooling)
Hands-on interest in applying LLMs and AI-native approaches to real engineering problems
Familiarity with continuous delivery and autonomous deployment practices
Bias for measurable impact and comfort inventing in an ambiguous, high-ownership charter
WANT TO BUILD AI SYSTEMS — NOT CARRY A PAGER?
Fulfillment by Amazon (FBA) lets sellers worldwide leverage Amazon's world-class logistics infrastructure — storage, fulfillment, delivery, returns — as a service. Sellers from Fortune 50 companies to hundreds of thousands of small businesses in 135+ countries rely on FBA, which powers tens of billions in annual GMS across dozens of categories.
Most engineering teams spend their best hours reacting — triaging tickets, babysitting deployments, answering the same operational questions over and over. We're building the opposite team. Our entire charter is to build the AI-native systems that make reactive work disappear: agents that resolve operational issues before a human sees them, self-healing pipelines that deploy without manual gates, and a knowledge foundation that lets software answer for itself. You won't be absorbing FBA's operational load — you'll be engineering it out of existence.
This is a VP-funded, multi-year charter with end-to-end ownership and a leadership-backed mandate. You'll work at the frontier of applied AI — LLM-powered remediation agents, machine-readable operational knowledge, autonomous deployment systems — and see your work adopted across 55+ teams and 500+ engineers. We operate with startup intensity inside Amazon: small teams, fast cycles, and the freedom to invent.
Why this team is different
Build systems, not backlog. Your job is to invent AI-native tooling — not to sit in an operational queue. Your work is measured by how much reactive toil it eliminates for other teams.
AI at the core, not bolted on. You'll ship LLM-powered remediation agents, autonomous workflows, and a knowledge foundation that makes AI-assisted development the default across FBA — real production systems, not prototypes.
Learn from the best. You'll join a dedicated pod with direct access to multiple senior and Principal SDEs for design guidance, code review, and mentorship — with a clear path to grow your scope and visibility on a VP-sponsored charter.
Provable impact. Your systems free up the equivalent of dozens of engineers across FBA — measured, visible, and tied directly to a leadership-backed goal.
What you'll build
Agentic remediation systems — LLM-powered agents that detect, diagnose, and resolve operational issues automatically, replacing manual runbooks with self-executing guidance.
Self-healing deployment platforms — safe primitives, automated integration testing, and pipeline intelligence that drive teams toward fully continuous, hands-off delivery.
The FBA knowledge foundation — the OE infrastructure and knowledge-graph tooling that let AI systems reason about FBA's services and answer operational questions autonomously.
Basic qualifications
3+ years of non-internship professional software development experience
Experience programming with at least one modern language (Java, C++, Python, etc.)
Experience contributing to the architecture and design (design patterns, reliability, scaling) of new and current systems
Experience with the full software development lifecycle — coding standards, code reviews, source control, build processes, testing, and operations
Preferred qualifications
Experience building automation, platform, or developer-productivity systems (CI/CD, observability, agentic/AI-assisted tooling)
Hands-on interest in applying LLMs and AI-native approaches to real engineering problems
Familiarity with continuous delivery and autonomous deployment practices
Bias for measurable impact and comfort inventing in an ambiguous, high-ownership charter
Key job responsibilities
Software Development Engineer II — AI-Native Engineering Systems, FBA
WANT TO BUILD AI SYSTEMS — NOT CARRY A PAGER?
Fulfillment by Amazon (FBA) lets sellers worldwide leverage Amazon's world-class logistics infrastructure — storage, fulfillment, delivery, returns — as a service. Sellers from Fortune 50 companies to hundreds of thousands of small businesses in 135+ countries rely on FBA, which powers tens of billions in annual GMS across dozens of categories.
Most engineering teams spend their best hours reacting — triaging tickets, babysitting deployments, answering the same operational questions over and over. We're building the opposite team. Our entire charter is to build the AI-native systems that make reactive work disappear: agents that resolve operational issues before a human sees them, self-healing pipelines that deploy without manual gates, and a knowledge foundation that lets software answer for itself. You won't be absorbing FBA's operational load — you'll be engineering it out of existence.
This is a VP-funded, multi-year charter with end-to-end ownership and a leadership-backed mandate. You'll work at the frontier of applied AI — LLM-powered remediation agents, machine-readable operational knowledge, autonomous deployment systems — and see your work adopted across 55+ teams and 500+ engineers. We operate with startup intensity inside Amazon: small teams, fast cycles, and the freedom to invent.
Why this team is different
Build systems, not backlog. Your job is to invent AI-native tooling — not to sit in an operational queue. Your work is measured by how much reactive toil it eliminates for other teams.
AI at the core, not bolted on. You'll ship LLM-powered remediation agents, autonomous workflows, and a knowledge foundation that makes AI-assisted development the default across FBA — real production systems, not prototypes.
Learn from the best. You'll join a dedicated pod with direct access to multiple senior and Principal SDEs for design guidance, code review, and mentorship — with a clear path to grow your scope and visibility on a VP-sponsored charter.
Provable impact. Your systems free up the equivalent of dozens of engineers across FBA — measured, visible, and tied directly to a leadership-backed goal.
What you'll build
Agentic remediation systems — LLM-powered agents that detect, diagnose, and resolve operational issues automatically, replacing manual runbooks with self-executing guidance.
Self-healing deployment platforms — safe primitives, automated integration testing, and pipeline intelligence that drive teams toward fully continuous, hands-off delivery.
The FBA knowledge foundation — the OE infrastructure and knowledge-graph tooling that let AI systems reason about FBA's services and answer operational questions autonomously.
Basic qualifications
3+ years of non-internship professional software development experience
Experience programming with at least one modern language (Java, C++, Python, etc.)
Experience contributing to the architecture and design (design patterns, reliability, scaling) of new and current systems
Experience with the full software development lifecycle — coding standards, code reviews, source control, build processes, testing, and operations
Preferred qualifications
Experience building automation, platform, or developer-productivity systems (CI/CD, observability, agentic/AI-assisted tooling)
Hands-on interest in applying LLMs and AI-native approaches to real engineering problems
Familiarity with continuous delivery and autonomous deployment practices
Bias for measurable impact and comfort inventing in an ambiguous, high-ownership charter
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
- 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