Amazon
Posted 2mo ago

Sr. Software Development Engineer, Products and Solutions

Amazon
New York, New York, United States
$185k-$250k/yrOnsiteFull Time
Responsibilities
  • owning architecture
  • writing code
  • mentoring engineers
Requirements
  • 5+ years professional software development and programming experience
  • 5+ years leading design/architecture
  • Mentoring or tech lead experience
  • ML/LLM fundamentals, and a bachelor's in computer science or equivalent
Technical tools mentioned
PythonAWS CDKReactBedrockStep FunctionsLambdaDynamoDBAPI GatewayAWS TransformLLMs

Job description

Description

We're looking for a Senior Software Development Engineer who wants to build AI-powered products that change how enterprises move to the cloud — and who thrives as the technical anchor of an AWS 2-pizza team.

You'll own the architecture and delivery of production systems that power how AWS Professional Services delivers enterprise cloud migrations and modernization at scale. Our team builds agentic AI solutions — platforms where AI agents and human consultants collaborate as a unified delivery team — reducing migration timelines from years to months and cutting costs dramatically. The work spans the full migration lifecycle: assessment, planning, orchestration, execution, and integration with AWS Transform (Amazon's agentic AI service for enterprise modernization). You'll be building real software used daily by thousands of practitioners serving Fortune 500 customers.

This is a hands-on builder role with leadership expectations. You'll write code, design systems, lead projects across multiple engineers, mentor teammates, and own operational excellence for your services — all within a product engineering org that ships fast and measures success by adoption and customer outcomes.

What We Build
Our platform is a multi-agent system that orchestrates enterprise cloud migrations end-to-end. Our business spans several domains:

- Agentic AI — AI agents that autonomously handle migration tasks (discovery, wave planning, runbook generation, infrastructure provisioning) while coordinating with human consultants
- Orchestration and workflow — the coordination layer that enables multiple agents and humans to work in parallel with shared context and minimal overhead
- Platform infrastructure — shared services (project datastores, external system connectors, agent lifecycle management) that underpin the PCAM ecosystem
- AWS Transform integration — bidirectional data and workflow connectivity with AWS's flagship enterprise modernization service
- Extensibility — frameworks that enable ProServe teams to build and deploy custom agents for specialized customer needs

All of it involves building agentic AI systems at production scale with real users and real constraints.

Why This Team
- You'll build, not consult — we're a product engineering org inside Professional Services. We own our roadmap, ship on our cadence, and maintain our services. This is not billable-hours consulting.
- AI-native problems — every team is working on some aspect of agentic AI: building agents, orchestrating them, evaluating their outputs, or making them extensible. You'll be at the frontier of applied AI engineering.
- Small team, big impact — as an AWS 2-pizza team, you'll have direct ownership of significant components. Your architecture decisions directly impact 5000+ consultants across 60+ countries delivering $1B+ in active delivery pipeline.
- Full-stack ownership — from React frontends to CDK infrastructure to AI agent logic. No artificial boundaries between "frontend" and "backend" engineers.
- Career growth — we invest in developing senior engineers toward Principal levels. You'll work alongside senior architects and receive direct mentorship on expanding your technical influence beyond a single team.
- Direct customer engagement — you'll occasionally engage directly on customer migrations, seeing your tools in action and bringing insights back to improve the platform.


Key job responsibilities
- Own team-level architecture — design systems that are simple, extensible, and operationally sound
- Influence design and technical decisions beyond your immediate team, contributing to org-wide architectural direction and engineering standards
- Lead projects spanning multiple engineers; make sound technical decisions and drive execution from design through production deployment
- Design and build agentic AI components — whether that's agent logic, orchestration workflows, evaluation pipelines, or integration APIs
- Write production code daily — you should spend the majority of your time building, not meeting
- Set engineering standards on your team: code quality, testing practices, CI/CD pipelines, observability, and incident response
- Solve complex distributed systems problems where trade-offs between latency, consistency, extensibility, and cost aren't obvious
- Proactively identify and resolve technical debt; simplify systems rather than layering complexity
- Mentor and grow engineers on your team; help junior and mid-level engineers level up through code reviews, design guidance, and career coaching
- Communicate technical designs clearly in writing — design docs, RFCs, and architecture decision records
- Drive operational excellence: meaningful alarms, runbooks, dashboards, and a culture of learning from incidents
- Travel ~5% to customer sites and partner team locations to understand how your tools perform in the field

A day in the life
Our Migration & Modernization Engineering group builds the agentic AI products that help AWS Professional Services deliver cloud migrations at scale. We're a product engineering team — not a consulting delivery org.

Tech stack: Python, AWS CDK, React, with heavy use of AWS services (Bedrock, Step Functions, Lambda, DynamoDB, API Gateway, and others). We're building on the latest agentic AI capabilities — expect to work with LLMs, multi-agent frameworks, and tool-use patterns daily.


About the team
We ship frequently, debate architecture in design docs (not committees), and believe great engineers stay close to the code. We're building something new and moving fast — if you want greenfield problems with real constraints, this is it.


ABOUT AWS:
 
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
 
Why AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. 

Inclusive Team Culture
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.

Mentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. 

Basic Qualifications

- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience as a mentor, tech lead or leading an engineering team
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution
- Bachelor's degree in computer science or equivalent

Preferred Qualifications

- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Experience building complex software systems that have been successfully delivered to customers

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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, NY, New York - 184,900.00 - 250,200.00 USD annually

About Amazon

Global online retail and cloud computing technology provider.

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