Gen AI Developer

Cognizant

Confirmed live today High trust

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 $182k

$133k $235k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $142,450–$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 · Gen AI Developer

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The Gen AI Developer will build and deploy production-ready generative artificial intelligence applications. The role focuses on developing agentic workflows and complex AI agents using large language models. Day-to-day responsibilities include creating RAG solutions that utilize embeddings, vector databases, semantic search, and document retrieval systems. The successful candidate will use Python, LangChain, LangGraph, and various APIs while applying prompt engineering techniques. Technical tasks involve integrating LLMs through platforms like Azure OpenAI, AWS Bedrock, or Google Vertex AI. The position requires practical experience with LLMOps, MLOps, evaluation frameworks, guardrails, and observability. This role solves technical challenges related to cloud deployment and the practical implementation of generative AI technologies within a production environment to ensure reliable and scalable model performance.

Skills

Python LLMs RAG LangChain LangGraph Azure OpenAI AWS Bedrock Google Vertex AI Vector Databases Prompt Engineering LLMOps MLOps APIs Embeddings Semantic Search Guardrails Observability Cloud Deployment

What you'll do

Build and deploy production-ready GenAI applications using LLMs, RAG, and agentic workflows.
Develop RAG solutions using embeddings, vector databases, and semantic search.
Integrate LLMs through platforms like Azure OpenAI, AWS Bedrock, or Google Vertex AI.
Implement prompt engineering techniques to optimize model outputs.
Manage LLMOps and MLOps processes including evaluation, guardrails, and observability.
Deploy AI models and applications to cloud environments.

What we're looking for

Build and deploy production-ready GenAI applications using LLMs, RAG, and AI agents/agentic workflows.
Possess strong hands-on experience with Python, LangChain/LangGraph, APIs, and prompt engineering.
Develop RAG solutions using embeddings, vector databases, semantic search, and document retrieval.
Integrate LLMs through platforms such as Azure OpenAI, AWS Bedrock, or Google Vertex AI.
Experience with LLMOps/MLOps, evaluation, guardrails, observability, and cloud deployment (preferred).

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