AI Architect

EPAM Systems; Chennai District; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

EPAM Systems seeks a highly skilled AI Architect to lead design, development and deployment of Generative AI solutions across cloud platforms, guiding architecture from concept to production.

You will design scalable GenAI systems, fine-tune models, integrate vector databases like FAISS and Qdrant, apply MLOps practices, ensure governance and ethical standards, and collaborate with cross-functional teams to deliver robust AI capabilities.

Qualifications

• 12+ years in AI/ML with 2+ years in Generative AI and LLMs.
• Expertise in neural networks: LSTM, CNN, VAE.
• Experience with LangChain, LlamaIndex, and Hugging Face.
• Skilled with PEFT, LoRA, QLoRA, and RAG pipelines.
• Familiarity with FAISS and Qdrant vector databases.
• Proficient in AWS, Azure, and GCP with MLOps.
• Strong problem-solving and cross-functional collaboration.
• English proficiency at B2+.

Responsibilities

• Design scalable architectures for GenAI solutions on cloud platforms.
• Develop, fine-tune, and productionize AI/ML models.
• Ensure governance, security, and ethical AI standards in model development and deployment.
• Collaborate with cross-functional engineering teams to deliver robust AI solutions.
• Optimize model performance through evaluation methods using tools like RAGAS and DeepEval.
• Integrate vector databases such as FAISS and Qdrant into AI pipelines.
• Utilize cloud AI platforms (AWS, GCP, Azure) to build scalable solutions.
• Apply MLOps practices to streamline development and deployment workflows.
• Leverage Generative AI tools including LangChain, LlamaIndex, Hugging Face, PEFT, LoRA, QLoRA, and RAG pipelines.
• Provide expertise on traditional deep learning methods including LSTM, CNN, and VAE.

Skills

Generative AI

LLMs

Agentic systems

Neural networks

LangChain

LlamaIndex

Hugging Face

PEFT

LoRA

QLoRA

RAG pipelines

FAISS

Qdrant

AWS

Azure

GCP

MLOps

LSTM

CNN

VAE

Tools

LangChain

LlamaIndex

Hugging Face

PEFT

LoRA

QLoRA

RAG pipelines

RAGAS

DeepEval

FAISS

Qdrant

AWS

Azure

GCP

MLOps

Job description

We are seeking a highly skilled AI Architect to lead the design, development, and deployment of cutting-edge Generative AI solutions, leveraging the latest tools, frameworks, and cloud platforms to solve complex challenges and drive innovation.

Responsibilities

• Design and implement scalable architectures for Generative AI solutions using state-of-the-art tools and cloud platforms
• Develop, fine-tune, and productionize Generative AI and traditional AI/ML models, ensuring optimal performance and stability
• Ensure compliance with governance, security, and ethical AI standards in model development and deployment
• Collaborate with cross-functional engineering teams to deliver seamless and robust AI solutions
• Optimize model performance through effective evaluation methods, leveraging tools like RAGAS and DeepEval
• Integrate vector databases such as FAISS and Qdrant into AI pipelines to enhance information retrieval and storage
• Utilize cloud AI platforms, including AWS, GCP, or Azure, to build scalable solutions
• Apply MLOps practices to streamline development and deployment workflows
• Leverage Generative AI tools including LangChain, LlamaIndex, Hugging Face, PEFT, LoRA, QLoRA, and RAG pipelines for advanced solution-building
• Provide expertise on traditional deep learning methods including LSTM, CNN, and VAE

Requirements

• 12+ years of experience in AI/ML with at least 2 years specializing in Generative AI, LLMs, and agentic systems
• Expertise in neural network architectures such as LSTM, CNN, and VAE
• Proficiency in advanced GenAI tools such as LangChain, LlamaIndex, and Hugging Face
• Skills in leveraging PEFT, LoRA, QLoRA, and RAG pipelines
• Familiarity with vector databases including FAISS and Qdrant
• Proficiency in cloud AI platforms such as AWS, Azure, and GCP, with a solid understanding of MLOps practices
• Knowledge of AI evaluation frameworks such as RAGAS and DeepEval
• Strong coding expertise and a proven problem-solving mindset
• Flexibility to work effectively in cross-functional engineering environments
• English proficiency at B2 level or higher