Six Figure Work

Sr. Software Development Engineer, AWS Forward Deployed Engineering

AWS

Company websiteaws.org (AWS, opens in new tab)

Base salary $184,900  to $250,200

Employer-published annual base salary, USD. Advertised base range in New York, NY

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  • LocationNew York, NY
  • WorkplaceWorkplace not stated
  • Status at last checkSource accepting applications when checked
  • Last checked (3 h ago) · observed since

About this job

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 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

Source: AWS · View original posting (opens in new tab)

Pay in context

This role's base floor ($184,900) is above 60% of the 960 Software Engineering roles in New York listed on this site; 24 others list the same floor. Their median floor is $175,000; the middle half runs from $145,000 to $200,000.

Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 6, 2026.

This range next to 6 other live AWS roles with the nearest advertised base floor
Chart as a table
This range next to 6 other live AWS roles with the nearest advertised base floor
RolePublished base
Sr. Software Development Engineer, AWS Forward Deployed Engineering (this listing)$184,900 - $250,200
Manager III, Software Dev - AMZ10119640$184,900 - $250,200
Sr. Software Dev Engineer, AI Security$184,900 - $250,200
Software Devevelopment Manager, AWS Tax Engine, AWS Invoicing$184,900 - $250,200
Senior Hardware Development Engineer, AWS Mainstream Compute$183,000 - $247,600
Sr Hardware Development Engineer, AWS Board Core Design and Services Team$183,000 - $247,600
Cloud HDE III - AMZ009953$183,000 - $247,600

Same $100K to $400K scale as every card. All AWS roles · How to read the bar

Observed changes

  1. Began meeting the published-salary criteria
  2. First observed on the employer's board
Observed since
Employer-stated posting date
2026-06-15
Where this pay comes from

Location as the employer wrote it: US, NY, New York

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

Method
Employer text, read with fixed rules and re-verified
Checked
Rule set
us-base-v2

The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.

What we verified

  • The pay figures come from the employer's own listing, quoted exactly above.
  • The pay is an annual base salary in US dollars with a minimum of at least $100,000.
  • The role was publicly listed on the employer's job board when last checked.

We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.