AI/ML Engineer – Generative AI & LLM - Mphasis - Charlotte, NC

We are looking for a highly skilled
*AI/ML Engineer – Module Lead**
with strong experience in
*Generative AI and Large Language Models (LLMs)**
. In this role, you will design, develop, and deploy scalable AI solutions leveraging advanced models such as
*GPT**
,
*LLaMA**
, and
*Gemini**
.
You will play a key role in building
*Retrieval-Augmented Generation (RAG) pipelines**
, optimizing AI model performance, and integrating AI capabilities into production systems.
This role is ideal for engineers passionate about building
*real-world Generative AI applications at scale**
.
Key Responsibilities
Develop and fine-tune*Large Language Models (LLMs)**
and Generative AI applications.
Design and implement*Retrieval-Augmented Generation (RAG) pipelines**
for intelligent knowledge retrieval.
Work with vector databases such as*Pinecone**
,
*Milvus**
, and
*Chroma**
.
Optimize AI models for*performance, latency, scalability, and cost efficiency**
.
Implement*AI safety and guardrails**
to ensure responsible and secure AI usage.
Collaborate with cross-functional teams including*data scientists, software engineers, and product teams**
to deploy AI solutions into production environments.
Stay updated with the latest advancements in*Generative AI, deep learning, and LLM technologies**
.
Document architecture, models, and best practices for scalability and knowledge sharing.
Required Skills
Strong expertise in*Artificial Intelligence and Machine Learning algorithms**
.
Hands-on experience working with*Large Language Models (LLMs)**
such as GPT, Llama, or Gemini.
Experience building*RAG pipelines**
and working with vector databases.
Proficiency in ML frameworks such as*PyTorch**
or
*TensorFlow**
.
Experience with LLM frameworks like*LangChain**
or
*LlamaIndex**
.
Strong understanding of*prompt engineering, model fine-tuning, and evaluation techniques**
.
Experience implementing*AI monitoring, governance, and safety controls**
.
Preferred Skills
Experience deploying AI solutions on clo