Your next challenge
Bring your AI engineering expertise to a role where you can turn complex commercial challenges into practical, scalable solutions. As an AI Agentic Engineer/ AI Forward Deployment Engineer, you’ll design and deploy cloud-native AI systems that help global business teams improve pricing and channel management. Working in a hybrid model, you’ll collaborate with product and business stakeholders, connect technical decisions to commercial outcomes, and see your solutions through from design to deployment.
What you’ll do
· Take ownership of AI-enabled solutions from design through deployment, using AWS Bedrock and major cloud platforms to tackle pricing and channel management challenges for global business units.
· Design secure, scalable environments across AWS, GCP, and Azure, supporting high-availability AI workflows and data pipelines for revenue optimization.
· Build reliable PHP backend services that connect cloud APIs and internal systems, bringing pricing rules and channel partner programs into operation.
· Use Python automation to connect data ingestion, model execution, and reporting—helping pricing teams spend less time on manual tasks and make decisions faster.
· Turn machine learning and generative AI capabilities into working Python applications, with the monitoring, logging, and error handling needed for consistent performance across hybrid environments.
· Work alongside pricing analysts and channel managers to translate their needs into solutions for margin management, discount structures, and partner incentives.
· Shape the dataflows behind pricing and channel management, creating clean data models, efficient storage, and timely access for analytics and day-to-day operations.
· Help establish coding standards, configuration management, and deployment practices that make AI and automation solutions easier to maintain, observe, and operate reliably.
· Tune cloud applications and automation workflows to meet latency, throughput, and cost-efficiency targets linked to commercial objectives.
· Partner with product, finance, and sales operations to validate outcomes and refine AI models using market feedback.
· Make your work reproducible by creating clear solution architectures, operational runbooks, and technical decision records that others can build on.
· Share your expertise with junior engineers through design reviews, pair programming, and guidance on cloud-native AI patterns.
· Build security, compliance, and governance into your cloud and automation work, reducing operational risk while supporting strategic pricing initiatives.
What you’ll bring
· Extensive experience designing and deploying AWS solutions, including hands-on use of AWS Bedrock and broader AWS services for production AI workloads.
· Strong practical expertise in at least one additional major cloud platform—GCP or Azure—with experience in networking, storage, identity, and managed data services.
· Solid PHP development skills, with the ability to build reliable REST-based services, integrations, and business logic for pricing and channel management workflows.
· Advanced Python and automation skills, including scripting libraries, testing frameworks, and orchestration tools for large-scale data and AI operations.
· Deep knowledge of pricing and channel management, including discount models, deal structures, partner tiers, and performance measurement.
· The ability to collaborate effectively in a hybrid, day-shift role, combining remote teamwork with onsite engagement to keep delivery moving.
What you can learn and develop
· Deepen your hands-on experience with AWS Bedrock and production AI workloads, while broadening your cloud engineering practice across AWS, GCP, and Azure.
· Develop your ability to take machine learning and generative AI applications into operation, with a focus on monitoring, reliability, security, and governance.
· Build a stronger understanding of how pricing strategies, discount structures, partner incentives, and channel programs influence commercial outcomes.
· Sharpen your automation and data engineering skills by connecting data ingestion, model execution, and reporting in Python-based workflows.
· Strengthen your stakeholder collaboration and technical leadership through cross-functional delivery, design reviews, pair programming, and mentoring junior engineers.
关于高知特 (Cognizant)
高知特(Cognizant)（纳斯达克代码：CTSH）作为一家AI Builder和相关技术服务提供商，致力于通过打造全栈AI解决方案，帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长，将企业独特的业务场景融入科技系统，赋能组织释放人才潜能，推动切实成果，并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情，敬请访问 cognizant.ai 或关注@cognizant。
补充雇佣信息
薪酬信息截至本职位发布之日为准。Cognizant 保留在适用法律允许的范围内随时修改该信息的权利。
申请人可能需要通过现场面试或视频会议的方式参加面试。此外，候选人在每次面试时可能需要出示其当前所在州或政府签发的有效身份证件。
Cognizant 是一家提供平等就业机会的雇主。在招聘过程中，您的申请和候选资格不会因种族、肤色、性别、宗教、信仰、性取向、性别认同、国籍、残疾、遗传信息、怀孕、退伍军人身份或任何其他受联邦、州或地方法律保护的特征而受到影响。
