GenAI Engineer: Build Production LLM Apps

Cognizant; Arkansas; On-site; USD 80,000 - 120,000; Full time

Benefits offered by this job

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

Job summary

Cognizant is seeking a GenAI Developer in the United States (Arkansas) to build and deploy production-ready GenAI applications using LLMs, RAG, and AI agents. You will work hands-on with Python, LangChain/LangGraph, APIs, and prompt engineering to develop RAG solutions with embeddings, vector databases, semantic search, and document retrieval.

Platforms include Azure OpenAI, AWS Bedrock, and Vertex AI. The role emphasizes LLMOps/MLOps, evaluation, guardrails, observability, and cloud deployment,

Qualifications

• Build and deploy GenAI apps using LLMs, RAG, and AI agents.
• Hands-on 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.

Responsibilities

• Build and deploy production-ready GenAI applications using LLMs, RAG, and AI agents/agentic workflows.
• Strong hands-on experience with Python, LangChain/LangGraph, APIs, and prompt engineering.
• Develop RAG solutions using embeddings, vector databases, semantic search, and document retrieval.

Skills

Python

LangChain

LangGraph

APIs

Prompt engineering

LLMs

RAG

Embeddings

Vector databases

Semantic search

Document retrieval

LLM integration

Azure OpenAI

AWS Bedrock

Vertex AI

LLMOps

MLOps

Guardrails

Observability

Cloud deployment

Tools

LangChain/LangGraph services

Azure OpenAI

AWS Bedrock

Google Vertex AI

Job description

Cognizant is seeking a GenAI Developer in the United States (Arkansas) to build and deploy production-ready GenAI applications using LLMs, RAG, and AI agents. You will work hands-on with Python, LangChain/LangGraph, APIs, and prompt engineering to develop RAG solutions with embeddings, vector databases, semantic search, and document retrieval.

Platforms include Azure OpenAI, AWS Bedrock, and Vertex AI. The role emphasizes LLMOps/MLOps, evaluation, guardrails, observability, and cloud deployment,