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.
Über Cognizant
Cognizant (NASDAQ: CTSH) i ist ein Technologiedienstleister und Entwickler von KI-Lösungen. Wir schlagen die Brücke zwischen KI-Investitionen und echtem unternehmerischem Mehrwert, indem wir ganzheitliche Full-Stack-KI-Lösungen für unsere Kunden entwickeln. Mit unserer fundierten Branchen-, Prozess- und Engineering-Expertise integrieren wir die spezifischen Anforderungen von Unternehmen passgenau in Technologiesysteme. So entfalten wir das menschliche Potenzial, erzielen greifbare Ergebnisse und sichern globalen Unternehmen in einer sich rasant wandelnden Welt den entscheidenden Vorsprung. Erfahren Sie mehr unter cognizant.ai oder @cognizant.
Zusätzliche Informationen zur Beschäftigung
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