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Cognizant

Gen AI Architect ( Agentic AI & LLM) (Remote)

Career Insights for Natural Language Processing Engineer

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What they do

A Natural Language Processing Engineer specializes in developing and implementing algorithms and models tailored for understanding, processing, and generating natural language text. They utilize methodologies such as tokenization, parsing, named entity recognition, part-of-speech tagging, and other NLP techniques to perform tasks including text classification, chatbot development, and other applications where the primary input or output is natural language text.

$121,879 / year median in the U.S.

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Job Description

Gen AI Architect (Agentic

AI & LLM

) (Remote) About the role As a Gen AI Architect ( Agentic

AI & LLM

) you will play a key role in designing and delivering next-generation AI-powered enterprise applications. You will lead the architecture and development of scalable Generative AI solutions, leveraging Large Language Models (LLMs), Agentic AI frameworks, modern web technologies, and distributed systems. Working across engineering, product, and business teams, you will define technical strategy, establish architectural standards, mentor engineers, and deliver innovative AI solutions that create measurable business value. In this role, you will: Architect and develop enterprise-scale Generative AI applications utilizing LLMs, RAG, structured data, workflow automation, and intelligent orchestration. Design and implement Agentic AI solutions using LangGraph, LangChain, or similar frameworks to support complex reasoning, memory management, tool integration, and human-in-the-loop workflows. Build scalable and fault-tolerant workflow orchestration solutions using Temporal or similar technologies. Define AI platform architectures covering model routing, prompt lifecycle management, observability, experimentation, governance, and production deployment. Establish evaluation frameworks for AI solutions, including offline testing, regression analysis, trace diagnostics, and business outcome measurement. Lead end-to-end product delivery, from architecture and development through deployment and operational support. Drive engineering best practices focused on scalability, performance, reliability, security, and maintainability. Mentor engineering teams and foster a culture of innovation, technical excellence, and continuous learning. Work model We strive to provide flexibility wherever possible. Based on this role's business requirements, this is a remote position open to qualified applicants in the United States. Regardless of your working arrangement, we are here to support a healthy work-life balance through our various wellbeing programs. The working arrangements for this role are accurate as of the date of posting. This may change based on the project you're engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations

•Please note that this position is not eligible for visa transfer or sponsorship now or at any time in the future

• What you need to have to be considered: 12+ years of experience designing and delivering large-scale distributed systems, enterprise platforms, or complex software applications. Proven success delivering production-grade AI and LLM-powered solutions, including agentic AI systems, RAG platforms, intelligent automation, or conversational AI applications. Deep expertise with Generative AI technologies including OpenAI models, prompt engineering, vector databases, retrieval frameworks, and AI orchestration patterns. Hands-on experience with LangGraph, LangChain, AutoGen, or similar agent development frameworks. Strong full-stack engineering background with expertise in ReactJS, Node.js, and modern application architecture. Demonstrated ability to define technical strategy, influence architecture decisions, and mentor engineering teams. Strong software engineering fundamentals, including system design, scalability, testing, performance optimization, and code quality practices. Bachelor's, Master's, or PhD degree in Computer Science, Engineering, or a related discipline, or equivalent practical experience. These will help you stand out: Experience building AI governance, observability, monitoring, and evaluation frameworks for enterprise environments. Expertise with workflow orchestration technologies such as Temporal. Experience implementing model experimentation, prompt versioning, and AI production rollout strategies. Knowledge of cloud-native architectures and enterprise-scale application modernization initiatives. Passion for emerging AI technologies and a demonstrated history of driving innovation across engineering organizations.

Salary and Other Compensation:

Applications will be accepted until October 9th, 2026. The annual salary for this position is between $ 102.600 to $162,500 depending on experience and other qualifications of the successful candidate. This position is also eligible for Cognizant's discretionary annual incentive program, based on performance and subject to the terms of Cognizant's applicable plans.

Benefits:

Cognizant offers the following benefits for this position, subject to applicable eligibility requirements: Medical/Dental/Vision/Life Insurance Paid holidays plus Paid Time Off 401(k) plan and contributions

Long-term/Short-term Disability Paid Parental Leave Employee Stock Purchase Plan Disclaimer:

The salary, other compensation, and benefits 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. Cognizant is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.

Benefits

  • Paid Time Off (PTO)
  • 401(k) Plans
  • Employee Stock Options (ESOs)
  • Health Insurance