Cognizant

AI/ML Engineer

Cognizant • $110K — $130K *
Bentonville, AR 72712In-Person
Consumer Technology
8 - 10 years of experience
Today
Be an Early Applicant
Job Overview by Ladders

Qualifications

  • Deep knowledge of large language models and generative AI for enterprise objectives.
  • Understanding of generative AI platform architecture for effective collaboration with engineers.
  • Strong grounding in AI and ML concepts, including model evaluation and feedback loops.
  • Data science expertise to interpret analytics and design user journeys for continuous improvement.
  • Experience in vendor management and retail to craft relevant workflows and information architectures.
  • Ability to communicate complex technical ideas simply to multidisciplinary teams.
  • Ten to fourteen years of experience in experience design or AI-enabled solutions.

Responsibilities

  • Design adaptive experience strategies using large language models and generative AI for personalized vendor journeys.
  • Develop interaction flows and service blueprints to enhance vendor productivity and operational transparency.
  • Create prototypes demonstrating generative AI applications for vendor management decision-making.
  • Collaborate with data science teams to define user-centric data models and ensure explainable insights.
  • Align experiences with enterprise AI architecture, focusing on scalability and responsible AI practices.
  • Analyze user data to refine concepts and measure AI feature impacts on vendor satisfaction and efficiency.
  • Facilitate design workshops to identify use cases for generative AI in vendor management processes.

Benefits

  • Hybrid work environment with day shifts and no travel required.
  • Opportunity to work with cutting-edge AI and ML technologies.
  • Collaborative culture with multidisciplinary teams.
  • Focus on inclusive and accessible design practices.
  • Engagement in meaningful projects that improve vendor management processes.
Full Job Description
Job Summary

Adaptive Experience Designer will craft intelligent user journeys that leverage concepts of large language models generative AI platform architecture AI and ML foundations and data science to deliver personalized omnichannel experiences in a hybrid work environment with day shifts and no travel focusing on scalable solutions for global retail vendor management ecosystems and measurable business outcomes.

Responsibilities
  • Design adaptive experience strategies that integrate concepts of large language models and generative AI to deliver highly contextual and personalized journeys across digital touchpoints for global retail vendor ecosystems.
  • Develop detailed interaction flows and service blueprints that translate complex AI and ML capabilities into intuitive experiences that enhance vendor productivity and operational transparency.
  • Create prototypes and experience artifacts that demonstrate how generative AI platform architecture can be used by vendor management stakeholders to make faster and more informed decisions.
  • Collaborate with data science teams to define user centric data models and experimentation plans that ensure recommendations and insights are explainable and trustworthy for business and vendor partners.
  • Align adaptive experiences with enterprise AI platform architecture by specifying experience layer requirements that support scalability reuse observability and responsible AI practices.
  • Analyze qualitative and quantitative user data to refine experience concepts and measure the impact of AI powered features on vendor satisfaction process efficiency and retail supply chain performance.
  • Define clear problem statements and success metrics for each AI driven experience initiative and maintain traceability between business outcomes user needs and technical implementation choices.
  • Facilitate discovery sessions and design workshops with product engineering and operations stakeholders to uncover use cases where generative AI and data science can meaningfully improve vendor management processes.
  • Document experience patterns content guidelines and conversational flows that guide how adaptive interfaces should respond across different scenarios while maintaining compliance and ethical standards.
  • Partner with product managers to build roadmaps where experiential milestones are explicitly linked to data readiness AI model maturity and platform architecture evolution.
  • Review and refine ML powered features before release by validating that stimuli responses and feedback loops align with defined experience principles and reduce friction for users.
  • Coordinate with retail vendor management specialists to ensure that adaptive experiences respect industry practices contractual constraints and operational realities in a hybrid work setting.
  • Champion inclusive and accessible design by ensuring that AI driven interactions accommodate diverse user preferences and reduce cognitive load for vendor and internal stakeholders.


Qualifications
  • Apply deep knowledge of concepts of large language models to design experiences that harness generative capabilities in controlled and purposeful ways aligned to enterprise objectives.
  • Use understanding of generative AI platform architecture to collaborate effectively with engineers on topics such as orchestration observability safety controls and integration with retail systems.
  • Demonstrate strong grounding in AI and ML concepts including supervised and unsupervised learning model evaluation and feedback loops to inform experience design decisions.
  • Leverage data science expertise to interpret analytical outputs define relevant metrics and design user journeys that promote continuous learning and model improvement.
  • Draw on vendor management retail exposure to craft workflows and information architectures that reflect typical vendor lifecycles performance evaluations and dispute resolution processes.
  • Communicate complex technical ideas in simple and actionable terms to multidisciplinary teams enabling shared understanding of how adaptive experiences will be implemented and measured.
  • Operate effectively in a hybrid work model using digital collaboration tools to co create artifacts document decisions and maintain alignment across geographically distributed stakeholders.
  • Maintain strong attention to detail and structured thinking developed over ten to fourteen years of professional experience in experience design AI enabled solutions or related fields.

Additional employment information
Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.

Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.

Applicants for US based positions must be currently authorized to work for any employer in the United States. The company is unable to provide employment-based immigration sponsorship for US based positions.

If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email [email protected] for roles based in the Americas or [email protected] for roles based in India.

About Cognizant

TriZetto is Powering Integrated Healthcare Management. With technology solutions touching more than half the U.S. population today, TriZetto is uniquely positioned to drive the convergence of core benefit administration, care management and constituent engagement. TriZetto provides premier information technology solutions that enable payers and other constituents in the healthcare supply chain to improve the coordination of benefits and care for healthcare consumers.

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Learn more about Cognizant
Size
340,400 employees
Market Cap
$28.7 billion
Industry
Information Technology
Net Income
$1.3 billion
Founded
1994
5 Year Trend
+6.5%
Revenue
$16.6 billion
NASDAQ
CTSH
* Ladders Estimates

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