AI Architect

EPAM Systems; Coimbatore District; On-site; INR 3,500,000 - 10,000,000; Full time

Job summary

EPAM Systems in India seeks an AI Architect to lead the design, development and deployment of Generative AI solutions. You will work across cloud platforms and modern AI stacks to deliver scalable, production-ready systems with strong governance.

Ideal candidates bring 12+ years in AI/ML, deep experience with LLMs and agentic systems, and hands-on proficiency in LangChain, Faiss, Qdrant and MLOps practices, while collaborating with cross-functional teams.

Qualifications

• 12+ years in AI/ML with at least 2 years in Generative AI, LLMs, and agentic systems.
• Expertise in neural network architectures such as LSTM, CNN, and VAE.
• Proficiency with GenAI tools like LangChain, LlamaIndex, and Hugging Face.
• Experience with PEFT, LoRA, QLoRA, and RAG pipelines.
• Familiarity with vector databases FAISS and Qdrant.
• Cloud platforms AWS/Azure/GCP with solid MLOps knowledge.
• Knowledge of AI evaluation tools such as RAGAS and DeepEval.
• Strong coding and problem-solving mindset; cross-functional work style.
• English proficiency at least B2.

Responsibilities

• Design scalable Generative AI architectures on cloud platforms.
• Develop, fine-tune, and productionize GenAI and traditional AI/ML models.
• Ensure governance, security, and ethical AI standards in development.
• Collaborate with cross-functional engineering teams to deliver robust AI solutions.
• Improve model performance via thorough evaluation methods.
• Integrate FAISS and Qdrant into AI pipelines for retrieval enhancements.
• Leverage AWS, GCP, and Azure to build scalable solutions.
• Apply MLOps practices to streamline development and deployment.
• Utilize LangChain, LlamaIndex, Hugging Face, PEFT, LoRA, QLoRA, RAG pipelines.
• Provide expertise on LSTM, CNN, and VAE.

Skills

Generative AI

LLMs

Agentic systems

Neural networks

MLOps

Python

Cloud platforms

English proficiency

Tools

LangChain

LlamaIndex

Hugging Face

FAISS

Qdrant

RAGAS

DeepEval

PEFT

LoRA

QLoRA

RAG pipelines

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