Native AI Engineer

Cognizant

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Quick summary

Work type
On-site
Location
Bentonville, AR
Posted
8 days ago
Freshness
Confirmed live today
Nearby
99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $186k
$123k $236k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $149,462–$222,500.

Based on 240 similar postings.

Employer

About Cognizant

Cognizant is a multinational IT services and consulting company offering digital transformation, technology, and business process services. It serves clients across financial services, healthcare, manufacturing, and other industries worldwide.

Cognizant currently has 330 open roles on FindRole.

Listed pay typically runs $100,000–$135,000 across 211 roles with salary data.

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At a glance

TL;DR · Native AI Engineer

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The Native AI Engineer will join the engineering team to build and deploy AI-native applications, copilots, and intelligent agents. The primary responsibilities involve developing solutions using Large Language Models like GPT, Claude, Gemini, and Llama while designing RAG pipelines with vector databases. The role requires integrating AI applications with enterprise data sources, APIs, and business systems to automate processes through prompts, workflows, and multi-agent solutions. Key technical requirements include proficiency in Python, experience with LangChain, LangGraph, CrewAI, or Semantic Kernel, and knowledge of embeddings and semantic search. Candidates must also understand REST APIs, cloud platforms like Azure, AWS, or GCP, and CI/CD processes. The position focuses on optimizing AI models for performance, accuracy, scalability, and cost efficiency within a business context.

Skills

Python Generative AI LLMs LangChain LangGraph CrewAI Semantic Kernel RAG Vector Databases Azure AWS GCP Docker Kubernetes CI/CD REST APIs Embeddings Semantic Search

What you'll do

  • Build and deploy AI-native applications, copilots, and intelligent agents.
  • Develop solutions using LLMs such as GPT, Claude, Gemini, or Llama.
  • Design and implement RAG pipelines with vector databases.
  • Integrate AI applications with enterprise data sources, APIs, and business systems.
  • Create prompts, workflows, and multi-agent solutions to automate business processes.
  • Optimize AI models for performance, accuracy, scalability, and cost efficiency.

What we're looking for

  • Strong proficiency in Python.
  • Experience with Generative AI and Large Language Models (LLMs).
  • Knowledge of RAG, vector databases, embeddings, and semantic search.
  • Experience with AI frameworks such as LangChain, LangGraph, CrewAI, or Semantic Kernel.
  • Understanding of AI agent development and orchestration.
  • Experience with REST APIs, cloud platforms (Azure, AWS, or GCP), and CI/CD processes.
  • Familiarity with Docker and Kubernetes.

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