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About This Role
DESCRIPTION
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Do you enjoy helping U.S. Intelligence Community and Defense agencies implement innovative cloud computing solutions and solve unique technical problems? Would you like to do this using the latest cloud technologies while becoming a core part of the largest cloud infrastructure on the planet? Amazon Web Services (AWS) is seeking a Systems Development Engineer I to own and advance mission\-critical services in our Amazon Dedicated Clouds (ADC).
We are looking for a Systems Development Engineer to work as part of a team that will help design, implement, and support resilient, high\-performance systems for government customers operating in air\-gapped regions. You'll be part of a truly innovative team in a fast\-paced environment that has the entrepreneurial feel of a start\-up. This is an opportunity to design, build, and operate systems on a massive scale, and to gain top\-notch experience in cloud computing. You'll be surrounded by people who are passionate about cloud computing and believe that world\-class service is critical to customer success.
The ideal candidate will:
- Be great fun to work with. Our company credo is "Work hard. Have fun. Make history". The right candidate will love what they do and instinctively know how to make work fun.
- Have strong Linux \& Networking Fundamentals. You should have deep experience working with Linux, preferably in a large\-scale, distributed environment. You understand networking technology and how servers and networks inter\-relate.
- Think Big. You will build and deploy solutions across thousands of devices. You will strive to improve and streamline processes to allow for work on a massive scale.
- Have experience in systems development, software engineering, or a related field.
- Possess strong technical skills in systems design, software development, operations, automation, and process improvement.
- Have exposure to designing and implementing technology solutions with a focus on resilience and scalability.
- Be proficient in at least one programming language and eager to learn cloud technologies.
- Have solid problem\-solving skills and the ability to break down complex issues into manageable components with guidance from senior engineers.
- Communicate effectively within your team and contribute to technical discussions.
- Have a passion for operational excellence and continuous improvement.
This position requires that the candidate selected must currently possess and maintain an active TS/SCI security clearance with polygraph. The position further requires the candidate to opt into a commensurate clearance for each government agency for which they perform AWS work.
Key job responsibilities
As a Systems Development Engineer you will:
- Contribute to the design and delivery of technology solutions that improve resilience, performance, and operational efficiency of our systems.
- Work on well\-defined components, applications, and technology solutions with guidance from senior engineers, while growing toward greater autonomy.
- Identify and escalate ambiguous problems and architectural deficiencies, contributing to solutions under the direction of more experienced team members.
- Participate in design, scoping, and prioritization discussions, learning to make technical trade\-offs and understand costs of proposed solutions.
- Participate in reviews of architecture, design, operations, and post\-incident analysis for your team.
- Troubleshoot problems by researching root causes and thoroughly resolving defects, seeking help when needed.
- Participate in an on\-call rotation to support mission\-critical services.
A day in the life
On a “typical” day, our engineers may dive deep to find the root cause of a customer issue, investigate why a metric is trending in the wrong direction, or discuss radical new approaches to automate operational processes. As a member of our team you will join a dedicated group of engineers who provide troubleshooting and operations support, and innovate to automate operational tasks.
About the team
AI/ML ADC
The AI/ML U.S. Amazon Dedicated Cloud (ADC) organization is a pioneering force in delivering secure, advanced artificial intelligence and machine learning solutions to government and enterprise customers operating in isolated, air\-gapped environments. Our mission is to empower these customers with cutting\-edge AI/ML capabilities while maintaining the highest standards of security and compliance. We enable reliable, efficient builds and operations for services like SageMaker, Comprehend, Translate, Transcribe, Textract, Rekognition, and Bedrock in US ADC regions.
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.
AWS Infrastructure Services (AIS)
AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee\-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness.
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.
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.
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.BASIC QUALIFICATIONS
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- Experience in automating, deploying, and supporting infrastructure
- Experience programming with at least one modern language such as Python, Ruby, Golang, Java, C\+\+, C\#, Rust
- Experience with Linux/Unix
- 1\+ years of administrative experience in networking, storage systems, operating systems and hands\-on systems engineering experience
- 1\+ years of non\-internship professional software development experience
- 1\+ years of designing or architecting (design patterns, reliability and scaling) of new and existing systems experience
- Current, active US Government Security Clearance of TS/SCI with Polygraph
PREFERRED QUALIFICATIONS
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- Experience with CI/CD pipelines build processes
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, VA, Arlington \- 99,100\.00 \- 160,000\.00 USD annually
USA, VA, Herndon \- 99,100\.00 \- 160,000\.00 USD annually
Salary Context
This $99K-$160K range is in the lower quartile for AI Product Manager roles in our dataset (median: $185K across 167 roles with salary data).
View full AI Product Manager salary data →Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 4,317 AI roles we're tracking, AI Product Manager positions make up 4% of the market. At Amazon Web Services, this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills Required
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $217,100 based on 471 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($129K) sits 40% below the category median. Disclosed range: $99K to $160K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Amazon Web Services AI Hiring
Amazon Web Services has 93 open AI roles right now. They're hiring across Research Scientist, AI/ML Engineer, AI Software Engineer, AI Product Manager. Positions span New York, NY, US, Arlington, VA, US, Cupertino, CA, US. Compensation range: $160K - $350K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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