Senior AI/ML Engineer, Agentic AI (Remote)

Cognizant; Frankfort (KY); Remote; USD 113,000 - 130,000; Full time

Benefits offered by this job

Medical/Dental/Vision/Life Insurance

401(k) plan

Paid holidays plus PTO

Parental Leave

Employee Stock Purchase Plan

Job summary

Cognizant is seeking a Senior AI/ML Engineer to design, build, and deploy enterprise AI solutions leveraging LLMs, Agentic AI, and RAG architectures. This remote role requires collaboration across teams to deliver scalable, secure, production-ready AI applications.

Responsibilities include building AI solutions with LLMs and agents, designing scalable architectures with memory and state management, evaluating models for hallucinations and performance, and deploying production systems with

Qualifications

• 8+ years of experience in AI/ML, Data Science, or Software Engineering.
• Strong understanding of machine learning algorithms, evaluation metrics, and model validation techniques.
• Expertise in Agentic AI concepts, including LLMs, RAG, memory, reasoning, and prompt engineering.
• Hands-on experience building AI solutions using OpenAI, Azure OpenAI, Anthropic, Gemini, or similar platforms.

Responsibilities

• Build AI solutions using LLMs, agents, and RAG frameworks.
• Design scalable AI architectures with workflow orchestration, memory, and state management.
• Evaluate AI systems for quality, hallucinations, regression, and agent effectiveness.
• Integrate enterprise data sources and develop intelligent AI workflows.
• Deploy and manage AI applications using LLMOps/MLOps best practices.

Skills

Agentic AI

Python

Model evaluation

LLMs

MLOps

Tools

LangChain

LangGraph

Semantic Kernel

LlamaIndex

OpenAI

Job description

Cognizant is seeking a Senior AI/ML Engineer to design, build, and deploy enterprise AI solutions leveraging LLMs, Agentic AI, and RAG architectures. This remote role requires collaboration across teams to deliver scalable, secure, production-ready AI applications.

Responsibilities include building AI solutions with LLMs and agents, designing scalable architectures with memory and state management, evaluating models for hallucinations and performance, and deploying production systems with