Senior AI/ML Engineer: Agentic AI & LLMs (Remote)

Cognizant; Topeka (KS); Remote; USD 113,000 - 130,000; 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 Senior AI/ML Engineer to design, build, and deploy enterprise AI solutions leveraging LLMs, Agentic AI, and RAG architectures. You will collaborate with cross-functional teams to deliver scalable, secure, and production-ready AI applications in a remote setting.

The role emphasizes hands-on development with OpenAI, Azure OpenAI, LangChain, and MLOps practices, plus strong focus on model evaluation, governance, and responsible AI.

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.

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

8+ years experience

LLM/Agentic AI

Python

Model evaluation

MLOps/LLMOps

Reasoning

OpenAI/Azure OpenAI

Tools

LangChain

LangGraph

Semantic Kernel

LlamaIndex

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. You will collaborate with cross-functional teams to deliver scalable, secure, and production-ready AI applications in a remote setting.

The role emphasizes hands-on development with OpenAI, Azure OpenAI, LangChain, and MLOps practices, plus strong focus on model evaluation, governance, and responsible AI.