Sr Customer Solutions Manager Migrations Modernizations Team jobs at Amazon in United States, East Palo Alto

As a Principal Investment Manager within AWS, you will work with venture capital firms (or angel investors) to accelerate portfolio company success. You'll work closely with key investors to unlock the full potential of their portfolio companies on AWS, enabling faster innovation and scaling. Your role focuses on creating meaningful initiatives between the investors, helping startups leverage cloud to achieve breakthrough growth. You'll combine deep technical understanding of cloud and emerging technologies, such as generative AI with business acumen to identify opportunities and ensure startups have access to the tools, expertise, and support needed to build world-changing products on AWS infrastructure.Key job responsibilities
Design and implement solutions that address specific startup and investor needsTrack program effectiveness and provide insights based on feedback and resultsAbout the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the 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.Mentorship & 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.Work/Life Balance

- 10+ years of experience in technology industry with focus on startups, ideally in combination with technical leadership roles
- Deep understanding of cloud computing architectures, services, and best practices and knowledge of generative AI technologies
- Ability to evaluate and guide early-stage and scaling companies
- Demonstrated success developing and executing business initiatives that drive measurable outcomes
- Bachelor's degree in technical or technical management field or equivalent experience

- Advanced degree (MBA or technical)
- Leadership experience at startups or at Venture Capital firms
- Experience building and scaling cloud-native applications from ground-up
- Strong analytical and technical assessment capabilities
- Experience with commercial aspects of fast-growing technical businesses
- Demonstrated ability to understand and evaluate emerging technologies
- Experience in multiple technical domains (AI/ML, Security, Infrastructure)

About Sponsored Products and BrandsKey job responsibilities
As a Software Development Engineer in Machine Learning, you will:
* Enhance the scalability, automation, and efficiency of large-scale training and real-time inference systems.
* Pioneer the development of LLM inference infrastructure to support next-generation GenAI workloads at Amazon Ads scale.
* Work closely with applied scientists to optimize the performance of machine-learning models and infrastructure, and implement end-to-end solutions.

- 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

- 5+ 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

Key job responsibilities
• Manage a team of Business Development Managers, including hiring and developing your team
• Drive revenue, adoption and market segment share for our product
• Earn trust of customers and recommend product solutions that fit their business needs
• Measure performance, articulate root-cause analysis and make recommendations for improvement areas
• Relay market needs and customer feedback to internal Amazon teams including Product Management and Technical
• Create program goals and metrics, track progress and manage through obstacles to achieve your objectives
• Assess risks, anticipate challenges and provide escalation management when necessary
• Meet or exceed targets for customer and/or feature spend adoptionA day in the life

- 10+ years of building and leading large teams and working in matrixed operating structures experience
- Bachelor's degree or equivalent
- Experience working and communicating with multiple stakeholders, C-level executives and cross functional teams or equivalent
- Experience in strategic thinking about business, enterprise software products, and new technology platforms and architectures or equivalent

- 5+ years of managing and developing high performance teams experience

Key job responsibilities
- Integrate with a diverse array of internally and externally developed hardware and software services
- Implement continuous integration and continuous deployment (CI/CD) pipelines
- Validate solutions via software-in-the-loop simulation- Develop infrastructure to support development, operations, and maintenance of low level software for warehouse automation systems

- Experience in automating, deploying, and supporting large-scale infrastructure
- Experience programming with at least one modern language such as Python, Ruby, Golang, Java, C++, C#, Rust
- Experience with Linux/Unix
- Experience with CI/CD pipelines build processes
- 2+ years of non-internship professional software development experience

- Experience with distributed systems at scale
- Bachelor's degree
- Experience utilizing AWS cloud solutions in a DevOps environment

You will work at the forefront of applied AI, developing methods for fine-tuning, reinforcement learning, and preference optimization, while helping create evaluation frameworks that ensure safety, reliability, and trust at scale. You will work backwards from the needs of advertisers—delivering customer-facing products that directly help them create, optimize, and grow their campaigns.Beyond building models, you will advance the agent ecosystem by experimenting with and applying core primitives such as tool orchestration, multi-step reasoning, and adaptive preference-driven behavior. This role requires working independently on ambiguous technical problems, collaborating closely with scientists, engineers, and product managers to bring innovative solutions into production.Key job responsibilities- Design and build agents to guide advertisers in conversational and non-conversational experience.
- Design and implement advanced model and agent optimization techniques, including supervised fine-tuning, instruction tuning and preference optimization (e.g., DPO/IPO).
- Curate datasets and tools for MCP.
- Build evaluation pipelines for agent workflows, including automated benchmarks, multi-step reasoning tests, and safety guardrails.
- Develop agentic architectures (e.g., CoT, ToT, ReAct) that integrate planning, tool use, and long-horizon reasoning.
- Prototype and iterate on multi-agent orchestration frameworks and workflows.- Stay current with the latest research in LLMs, RL, and agent-based AI, and translate findings into practical applications.

- PhD, or Master's degree and 6+ years of applied research experience
- 3+ years of building machine learning models for business application experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.

About Sponsored Products and BrandsKey job responsibilities
As an Applied Science Manager, you will:* Directly manage and lead a cross-functional team of Applied Scientists, Machine Learning Engineers, and Software Development Engineers.
* Develop science and engineering roadmaps for SPB ads CTR prediction with ML and Gen AI solutions, run annual planning, and foster cross-team collaboration on model development and integration to advertising applications.
* Hire and develop top talent, provide technical and career development guidance to scientists and engineers within and across the organization.
* Stay informed about recent scientific publications, industrial research trends, and system designs that are pertinent to the SPB advertising business and bring those insights with the team.

- 4+ years of applied research experience
- 3+ years of scientists or machine learning engineers management experience
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Knowledge of ML, NLP, Information Retrieval and Analytics
- Experience programming in Java, C++, Python or related language

We are looking for technical builders who love the idea of working with early stage startups to help them as they grow. In this role, you’ll work directly with a variety of interesting customers and diagnostics startups) and help them make the best (and sometimes the most pragmatic) technical decisions along the way. You’ll have a chance to build enduring relationships with these companies and establish yourself as a trusted advisor.As a member of the Generative AI Startups team, you will work directly with customers to help them successfully leverage AWS technology to develop, train, tune, and deploy the next generation of generative AI foundation models at scale.As well as spending time working directly with customers, you’ll also get plenty of time to learn new technologies and keep your skills fresh. We have 200+ services across a range of different categories and it’s important that we can help startups take advantages of the right ones. You’ll also play an important role as an advocate with our product teams to make sure we are building the right products and features for the startups you work with. And for the customers you don’t get to work with on a 1:1 basis you’ll share knowledge more broadly by working on technical content and presenting at events.Key job responsibilities
-Help a diverse range of generative AI-focused startups to adopt the right architecture at each part of their lifecycle
-Support startups in architecting scalable, reliable and secure solutions
-Establish and build technical relationships within the startup ecosystem, including accelerators, incubators and VCsA day in the life
About the team
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
Work/Life BalanceMentorship 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.

- 8+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
- 3+ years of design, implementation, or consulting in applications and infrastructures experience

- 5+ years of infrastructure architecture, database architecture and networking experience
- Experience working with end user or developer communitiesPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.