Careers

The Agentic Automated Reasoning Group is building the next generation of software verification tools combining advances in artificial intelligence, the computational capacity of the cloud, and our deep expertise in the domain. Join us if you want to be a part of this transformational endeavor. The Strata team (https://github.com/strata-org) is seeking an applied scientist with broad interest and expertise in model checking, interactive theorem proving, programming language semantics, and generative AI. You will combine your expertise with that of your coworkers to build new tools that solve code analysis problems previously considered beyond reach. Our application areas span all the way from Infrastructure as Code to high-performance cryptography written in assembly code, while our methods span from interactive theorem proving to automated test generation. Each day, hundreds of thousands of developers make billions of transactions worldwide on AWS. They harness the power of the cloud to enable innovative applications, websites, and businesses. Using automated reasoning technology and mathematical proofs, AWS allows customers to answer questions about security, availability, durability, and functional correctness. We call this provable security, absolute assurance in security of the cloud and in the cloud. https://aws.amazon.com/security/provable-security/ Key job responsibilities Work with customer teams to understand the nature of their software and the properties they need to establish of it. Identify tools and methods capable of addressing the verification needs of customers, including any novel analysis capabilities required. Use techniques spanning property-based testing to model checkers, and interactive theorem provers to establish program properties. Explore generative AI techniques to help customers formalize their requirements, find revealing tests, generate required boiler plate for testing and model checking, and find and repair program proofs. About the team The Agentic Automated Reasoning Group at AWS develops and applies state of the art formal methods and automated reasoning techniques to ensure the security, reliability, and correctness of AWS services and customer applications, with a strong focus on AI based agents. Our work innovates tools and services to perform verification at scale and apply them to build safe and secure systems at AWS. We are also pioneering the use of formal verification and automated reasoning to develop agentic systems, ensuring AI agents operate within defined safety boundaries.

Join the next revolution in robotics at Amazon's Frontier AI & Robotics team, where you'll work alongside world-renowned AI pioneers to lead key initiatives in robotic intelligence. As a Member of Technical Staff, you'll spearhead the development of breakthrough foundation models that enable robots to perceive, understand, and interact with the world in unprecedented ways. You'll drive technical excellence in areas such as perception, manipulation, science understanding, sim2real transfer, multi-modal foundation models, and multi-task learning, designing novel algorithms that bridge the gap between state-of-the-art research and real-world deployment at Amazon scale. In this role, you'll combine hands-on technical work with scientific leadership, ensuring your team delivers robust solutions for dynamic real-world environments. You'll leverage Amazon's vast computational resources to tackle ambitious problems in areas like very large multi-modal robotic foundation models and efficient, promptable model architectures that can scale across diverse robotic applications. Key job responsibilities - Lead technical initiatives in robotics foundation models, driving breakthrough approaches through hands-on research and development in areas like open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, sim2real/real2sim techniques, end-to-end vision-language-action models, efficient model inference, video tokenization - Design and implement novel deep learning architectures that push the boundaries of what robots can understand and accomplish - Guide technical direction for specific research initiatives, ensuring robust performance in production environments - Mentor and support fellow scientists while maintaining strong individual technical contributions - Collaborate with engineering teams to optimize and scale models for real-world applications - Influence technical decisions and implementation strategies within your area of focus A day in the life - Develop and implement novel foundation model architectures, working hands-on with our extensive compute infrastructure - Guide and support fellow scientists in solving complex technical challenges, from sim2real transfer to efficient multi-task learning - Lead focused technical initiatives from conception through deployment, ensuring successful integration with production systems - Drive technical discussions within your team and with key stakeholders - Conduct experiments and prototype new ideas using our massive compute cluster - Mentor team members while maintaining significant hands-on contribution to technical solutions Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through ground breaking foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.

Have you ever wondered how Amazon launches and maintains a consistent customer experience across hundreds of countries and languages it serves its customers? Are you passionate about data and mathematics, and hope to impact the experience of millions of customers? Are you obsessed with designing simple algorithmic solutions to very challenging problems? If so, we look forward to hearing from you! At Amazon, we strive to be Earth's most customer-centric company, where both internal and external customers can find and discover anything they want in their own language of preference. Our Translations Services (TS) team plays a pivotal role in expanding the reach of our marketplace worldwide and enables thousands of developers and other stakeholders (Product Managers, Program Managers, Linguists) in developing locale specific solutions. Amazon Translations Services (TS) is seeking an Applied Scientist to be based in our Seattle office. As a key member of the Science and Engineering team of TS, this person will be responsible for designing algorithmic solutions based on data and mathematics for translating billions of words annually across 130+ and expanding set of locales. The successful applicant will ensure that there is minimal human touch involved in any language translation and accurate translated text is available to our worldwide customers in a streamlined and optimized manner. With access to vast amounts of data, State-of-the-art technology, and a diverse community of talented individuals, you will have the opportunity to make a meaningful impact on the way customers and stakeholders engage with Amazon and our platform worldwide. Together, we will drive innovation, solve complex problems, and shape the future of e-commerce. Key job responsibilities * Apply your expertise in LLM models to design, develop, and implement scalable machine learning solutions that address complex language translation-related challenges in the eCommerce space. * Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to define project requirements, establish success metrics, and deliver high-quality solutions. * Conduct thorough data analysis to gain insights, identify patterns, and drive actionable recommendations that enhance seller performance and customer experiences across various international marketplaces. * Continuously explore and evaluate state-of-the-art modeling techniques and methodologies to improve the accuracy and efficiency of language translation-related systems. * Communicate complex technical concepts effectively to both technical and non-technical stakeholders, providing clear explanations and guidance on proposed solutions and their potential impact. About the team We are a start-up mindset team. As the long-term technical strategy is still taking shape, there is a lot of opportunity for this fresh Science team to innovate by leveraging Gen AI technoligies to build scalable solutions from scratch. Our Vision: Language will not stand in the way of anyone on earth using Amazon products and services. Our Mission: We are the enablers and guardians of translation for Amazon's customers. We do this by offering hands-off-the-wheel service to all Amazon teams, optimizing translation quality and speed at the lowest cost possible.

Amazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. From personalized music playlists to exclusive podcasts, concert livestreams to artist merch, Amazon Music is innovating at some of the most exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service: Prime members get access to all the music in shuffle mode, and top ad-free podcasts, included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited, on-demand access to 100 million songs, including millions in HD, Ultra HD, and spatial audio; and anyone can listen for free by downloading the Amazon Music app or via Alexa-enabled devices. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale. The Data, Insights, Science and Optimization, Music Product and Tech (DISCO M&G) team is looking for a Data Scientist to join a team of scientists and engineers who analyze big data, provide analytics and insights and build models and algorithms to power Music product experiences. In this role, you will set the science vision and direction for the team and collaborate with internal stakeholders across marketing tech, Product , science and finance to scale and advance our science offerings. You will lead large scale science solutions, prioritize across multiple stakeholders and projects and be part of a fast-paced, dynamic and fun environment. Key job responsibilities • Lead the research and development of models and science products powering customer identity, acquisition, and retention strategies for Amazon Music • Partner with Marketing and Growth leadership to develop science-driven business strategies, including subscriber segmentation, lifecycle management, and upsell programs • Build predictive models — including propensity, uplift, and causal inference models — to support targeted marketing initiatives, measure incremental impact, and automate deep dives into key metric variances • Collaborate with product, engineering, and marketing teams to evaluate the impact of growth campaigns, features, and algorithmic interventions through rigorous experimentation • Analyze experiment results and provide data-driven recommendations to optimize subscriber acquisition and retention outcomes • Partner with Senior Data Scientists and Product Managers to define, propose, and validate success and guardrail metrics for identity and growth programs • Educate marketing and growth teams on analytics, measurement frameworks, and experimentation best practices, encouraging a culture of evidence-based decision making About the team The DISCO team focuses on accelerating Amazon Music customer growth by empowering product teams to make sound, customer-centric decisions through data and insights. We build data pipelines, self-service analytics, insights and predictive models enabling acquisition, engagement and retention at scale with personalized customer touchpoints.

In this role, you will design and build intelligent multi-agent systems that automate root cause analysis for advertising campaign delivery at scale. You will architect agentic orchestration patterns where specialized sub-agents (campaign diagnostics, deal-level troubleshooting, pacing control) are invoked as composable tools by a reasoning layer that determines which subsystems to query based on the nature of the issue. You will develop hierarchical analysis frameworks that move from daily trend detection to intra-day anomaly isolation, enabling the system to pinpoint when and why delivery degraded rather than relying on static time windows. You will build self-learning feedback loops where the system identifies recurring failure signatures (auction dynamics, pacing anomalies, supply contention), updates its diagnostic knowledge as engineering teams deploy fixes, and retires stale patterns automatically. We are looking for a passionate Applied Scientist with technical expertise in LLM-based agent architectures, retrieval-augmented generation, time-series anomaly detection, and production ML systems. In addition to hands-on experience building agentic AI solutions, an ideal candidate should demonstrate the ability to translate complex distributed system behaviors into structured diagnostic reasoning, show a willingness to push the boundaries of how LLMs interact with real-time operational data, and thrive in an environment where you ship production systems that directly reduce advertiser escalation time from days to minutes. Key job responsibilities * Conduct deep data analysis to derive insights for the business, identify gaps, and uncover new opportunities. * Develop scalable and effective machine learning models and optimization strategies to solve business problems. * Run regular A/B experiments, gather data, and perform statistical analysis to optimize advertiser experiences. * Collaborate closely with software engineers to deliver end-to-end solutions into production. * Enhance the scalability, efficiency, and automation of large-scale data analytics, model training, deployment, and serving. * Research and implement new machine learning models and techniques to improve advertising performance. A day in the life Your primary focus is building a multi-agent diagnostic system that automates root cause analysis for advertising campaign delivery issues. On a typical day, you might review how the system handled recent escalations, identify where it reasoned incorrectly, adjust orchestration logic, and write new evaluation cases. You will design agent architectures that invoke specialized sub-agents as tools, build hierarchical analysis frameworks that move from trend detection to anomaly isolation, and develop self-learning loops that keep the system's diagnostic knowledge current as the underlying platform evolves. You will work closely with SDEs building the diagnostic platform, product managers defining the troubleshooting experience, and the support teams who rely on your system to resolve advertiser delivery issues in minutes instead of days. Beyond the core agent work, you may find yourself diving into causal inference to measure recommendation effectiveness, prototyping proactive anomaly detection, or contributing to evaluation science for systems that reason over complex operational data. About the team The Demand Enablement, Product Analytics and Operations team builds the diagnostic and intelligence layer for Amazon DSP, the demand-side platform powering Amazon's programmatic advertising business. We own the systems that detect, diagnose, and surface delivery issues across campaigns, giving internal teams and advertisers the visibility to act before problems impact spend. Our product portfolio spans automated troubleshooting platforms, advertiser-facing delivery insights, and AI-powered root cause analysis using multi-agent architectures on foundation models. We are a small, high-ownership team that ships production systems end-to-end, from data pipelines processing billions of bid events to LLM-based agents that reason over complex advertising systems. If you want to work at the intersection of applied science, distributed systems observability, and real business impact measured in advertiser dollars recovered, this is the team.

About the Team Our team builds and operates automated reasoning technology that powers security and privacy assurance across Amazon and AWS at scale. Our technology is deeply integrated into critical Amazon and AWS security workflows. We operate at the intersection of automated reasoning, program analysis, and applied security — and our work directly impacts the security posture of every AWS service. About the Role We are looking for an experienced Applied Science Manager to lead the team's static analysis platform science team. In this role, you will own the technical vision and roadmap for our automated reasoning engine's static analysis capabilities, drive innovation in scalable program analysis, and lead a team of applied scientists working at the frontier of automated reasoning for security while also contributing technically as a player/coach. You will partner closely with security, privacy, and compliance stakeholders across AWS to expand the reach and impact of provably correct code analysis. You will also partner closely with automated reasoning experts across the company and contribute to the science of security Key job responsibilities Technical Leadership: Own the science roadmap for our automated reasoning engine, including taint analysis, compositional heap analysis, modular method summarization, and dataflow graph generation Hands-on Contribution: Personally contribute to key research and design decisions, including prototyping novel analyses and reviewing technical artifacts Team Building & Management: Hire, develop, and retain a world-class team of applied scientists; foster a culture of scientific rigor, innovation, and operational excellence Product Integration: Partner with application security and service teams to expand our platform's integration footprint and deliver new security and privacy analysis capabilities Research & Innovation: Advance the state of the art in static program analysis, including exploring formal verification of analysis correctness (e.g., using Lean, Coq, or Dafny), expanding language support beyond Java, and developing novel analysis techniques for emerging security properties Stakeholder Engagement: Collaborate with AWS AppSec, Privacy Engineering, and service teams to understand their security assurance needs and translate them into analysis capabilities Strategic Influence: Represent our team in the broader Automated Reasoning community at Amazon; contribute to automated reasoning initiatives, and academic partnerships About the team Our team builds and operates automated reasoning technology that powers security and privacy assurance across Amazon and AWS at scale. Our automated reasoning engine is the core technology behind our managed dataflow mapping service, which automatically tracks how data flows through AWS service teams’ code and infrastructure. Our technology is deeply integrated into critical Amazon and AWS security workflows. We operate at the intersection of automated reasoning, program analysis, and applied security — and our work directly impacts the security posture of every AWS service. Diverse Experiences Amazon Security 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. Why Amazon Security? At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & 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, training, and other career-advancing resources here to help you develop into a better-rounded professional. 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. This position will be part of the Conversational Ad Experiences team within the Amazon Advertising organization. Our cross-functional team focuses on designing, developing and launching innovative ad experiences delivered to shoppers in conversational contexts. We utilize leading-edge engineering and science technologies in generative AI to help shoppers discover new products and brands through intuitive, conversational, multi-turn interfaces. We also empower advertisers to reach shoppers, using their own voice to explain and demonstrate how their products meet shoppers' needs. We collaborate with various teams across multiple Amazon organizations to push the boundary of what's possible in these fields. We are seeking a science leader for our team within the Sponsored Products & Brands organization. You'll be working with talented scientists, engineers, and product managers to innovate on behalf of our customers. An ideal candidate is able to navigate through ambiguous requirements, working with various partner teams, and has experience in generative AI, large language models (LLMs), information retrieval, and ads recommendation systems. Using a combination of generative AI and online experimentation, our scientists develop insights and optimizations that enable the monetization of Amazon properties while enhancing the experience of hundreds of millions of Amazon shoppers worldwide. If you're fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey! Key job responsibilities - Serve as a tech lead for defining the science roadmap for multiple projects in the conversational ad experiences space powered by LLMs. - Build POCs, optimize and deploy models into production, run experiments, perform deep dives on experiment data to gather actionable learnings and communicate them to senior leadership - Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production. - Work closely with product managers to contribute to our mission, and proactively identify opportunities where science can help improve customer experience - Research new machine learning approaches to drive continued scientific innovation - Be a member of the Amazon-wide machine learning community, participating in internal and external meetups, hackathons and conferences - Help attract and recruit technical talent, mentor scientists and engineers in the team

Join us at the forefront of Amazon's sustainability initiatives to work on environmental and social advancements that support Amazon's long-term worldwide sustainability strategy. At Amazon, we're working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people who are passionate about making a meaningful impact on communities and the environment while helping shape the future of sustainable business practices. Sustainability Science and Innovation (SSI) is a multi-disciplinary team within WW Sustainability combining science, analytics, economics, statistics, machine learning, product development, and engineering expertise. We use data across the sustainability imperatives (carbon, water, waste, biodiversity, environmental risk and more) and these skills and capabilities to identify, develop, experiment, and scale the scientific solutions and innovations necessary for Amazon, customers and partners to help them solve their hardest unmet and evolving sustainability needs and goals. The Worldwide Sustainability (WWS) organization is seeking an exceptional scientific leader to join Amazon's Sustainability Science and Innovation team as a Researcher Scientist for Materials Chemistry Innovation. This role focuses on hands-on experimental research in materials chemistry to accelerate the discovery and validation of sustainable materials through systematic synthesis, characterization, and performance testing. You will lead the design and execution of experimental research campaigns targeting catalysts, functional materials, and sustainability-relevant chemistries across multivariate parameter spaces. You will establish scientific strategy and technical roadmaps for materials discovery while leading research initiatives that tackle complex sustainability challenges in critical industrial sectors. This position requires driving breakthrough solutions in materials synthesis and characterization through internal capabilities and strategic partnerships with universities, industry scientists, and government laboratories. You will mentor junior scientists and engineers while collaborating across Amazon's Innovation Lab Network to translate research into scalable solutions. Your leadership will be essential in developing early-stage, cost-effective materials that address significant technical and economic challenges fundamental to Amazon's operations, requiring you to navigate complex trade-offs between immediate deliverables and long-term environmental impact. You will also shape how emerging automation and AI tools are applied to accelerate materials discovery workflows. The ideal candidate demonstrates extensive experience in materials synthesis, advanced characterization techniques, and systematic experimental design for performance validations. You must possess proven ability to lead cross-functional teams, establish research priorities, and drive scientific innovation from concept to implementation. Deep technical expertise in materials testing methods, combined with strategic vision for translating research into practical applications is essential. Experience with high-throughput and combinatorial experimental approaches to efficiently explore large design spaces is highly valued. Your work will establish new paradigms in sustainable materials discovery through rigorous experimental research and performance testing, directly contributing to Amazon's sustainability goals while creating scalable solutions that extend beyond the company's immediate operations. Key job responsibilities - Develop scientific models that help solve complex and ambiguous sustainability problems, and extract strategic learnings from large datasets. - Work closely with applied scientists and software engineers to implement your scientific models. - Support early-stage strategic sustainability initiatives and effectively learn from, collaborate with, and influence stakeholders to scale-up high-value initiatives. - Support research and development of cross-cutting technologies for industrial decarbonization, including building the data foundation and analytics for new AI models. - Drive innovation in key focus areas including packaging materials, building materials, and alternative fuels. About the team Diverse Experiences: World Wide Sustainability (WWS) 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. Inclusive Team Culture: 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. 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.

As a Data Scientist on the Shopbop/Zappos Catalog Tech team, you will design and implement scientific approaches to revolutionize how we manage and enhance our product catalog data for our world-class selection of Shoes, Kids, and Active wear. You will work with Zappos' Senior leadership team to solve complex data challenges through advanced analytics and machine learning - creating innovative solutions and influencing product decisions through data-driven insights. You will lead critical initiatives to reduce catalog errors, accelerate product data capture, and develop state-of-the-art image classification systems for fashion features. You will partner daily with engineering teams and business stakeholders to provide expert guidance on model selection and implementation. As a member of the Zappos technical staff, you will leverage machine learning technologies and have access to industry leaders in AI/ML and E-Commerce to help grow your expertise. You will also routinely collaborate with data science teams across our sister companies at Amazon.com and Shopbop.com. You will push the boundaries of what's possible with applied machine learning and bring innovative solutions to bear for customers (including computer vision, NLP, and advanced ML models). You will think big about how data science can transform our catalog operations and be persistent in delivering robust, scalable solutions. Key job responsibilities Design and implement machine learning approaches to improve catalog data quality. Develop and validate scientific methodologies for automated data capture and classification. Partner with engineering teams to integrate ML models into production systems. Create and present analysis that drives decision-making at the senior leadership level. A day in the life You start the day reviewing model performance metrics, noting some drift in the image classification system that needs investigation. You spend the morning developing a new approach to reduce product attribute errors using recent advances in LLMs. In the afternoon, you meet with engineering teams to advise on model architecture for a new feature, and wrap up by analyzing the results of your latest A/B test on data capture efficiency improvements. About the team Zappos/Shopbop Catalog Tech team owns the software that drives our photostudio, product cataloging, and integration to Amazon's marketplace. We use Amazon's Leadership Principals and Engineering Expertise but have our own fun vibe. We are located in Madison WI, and Las Vegas NV.

The Amazon Web Services (AWS) Certification team is seeking a Psychometrician with experience working with criterion-referenced assessment programs to support a large global AWS Certification and Credentialing program. You will work closely with a team of psychometricians, subject matter experts, certification exam program managers, publishing, delivery, security, and product management teams to support ongoing analyses of exam and credential data. To be successful in this position, you must be highly motivated, creative, detail oriented, and a self-starter who is able to think big, execute, ensure high quality, yet stay focused on the details. Key job responsibilities Perform and support the main psychometric aspects of exam development and operations, including but not limited to automated test assembly, item and test analyses, optimal item bank design, job task analysis, standard setting, quality assurance, and project planning. Conduct main aspects of psychometric analysis in operational work including performing item analysis using psychometric methods, building optimal test forms and pools via optimization techniques, analyzing and monitoring item bank health, setting pass standards via standard setting studies, and supporting Job Task Analysis (JTA) to define and refresh test blueprints. Conduct main aspects of psychometric analysis in developing and applying statistical and psychometric modeling to evaluate and ensure AWS certification exams’ validity, reliability, applicability, efficiency, and accuracy. Participate in research projects to improve existing operational processes and quality using advanced techniques such as Machine Learning (ML), statistical modeling, Natural Language Processing (NLP), Generative Artificial Intelligence (GenAI), etc. Develop automation code using R or Python for psychometric workflow pipeline and other tasks to improve operational efficiencies. Present, interpret, and communicate the results of analyses to stakeholders through written and oral reports. Follow the accreditation standards set by ISO/IEC:2012 17024 and the National Council for Certifying Agencies (NCCA) as they relate to valid psychometric practices. Engage with the professional community through conferences and publications.