Artificial Intelligence Architect

Job Title: AI Architect

Location: Kolkata

Experience: 8+ Years

Role Overview:

We are seeking an experienced and visionary AI Architect with deep expertise in Generative AI, Multimodal AI Systems, and Enterprise AI Solution Design. The ideal candidate will lead the architecture, design, and implementation of advanced AI platforms powered by Large Language Models (LLMs), Graph RAG, Agentic RAG, Diffusion Models, and Multimodal AI frameworks.

The role requires strong hands-on experience in designing scalable AI ecosystems, optimizing vector databases and retrieval systems, implementing intelligent agent workflows, and building high-performance AI architectures for enterprise applications. Candidates should possess strong technical leadership capabilities along with advanced proficiency in Python, distributed AI systems, and cloud-native AI deployment.

In addition, the role demands specialized expertise in:

• LLMWiki and knowledge-driven AI systems

• Graph RAG and Agentic RAG architectures

• Diffusion Models for synthetic data generation and AI automation

• Vector DB integration and vector optimization techniques

• Multimodal AI (text, image, audio)

• Graph topology and layout-based reasoning systems

• Image layout analysis for document intelligence

• Search boosting and advanced retrieval optimization

Key Responsibilities:

AI Architecture & Solution Design

• Design and architect enterprise-grade Generative AI and Multimodal AI platforms.

• Build scalable LLM-powered systems using advanced RAG, Graph RAG, and Agentic RAG architectures.

• Define AI system architecture, model orchestration, and intelligent agent workflows.

• Develop AI knowledge frameworks leveraging LLMWiki and graph-based contextual reasoning.

Generative AI & Multimodal Systems

• Lead the development of applications powered by Large Language Models (LLMs), transformers, and multimodal models.

• Architect solutions integrating text, image, and audio processing pipelines.

• Design and implement Diffusion Model-based systems for synthetic data generation, automation, and testing workflows.

• Build advanced image layout analysis pipelines for document understanding and structured content interpretation.

Vector Database & Retrieval Optimization

• Architect and optimize vector search ecosystems using Pinecone, FAISS, Milvus, ChromaDB, or similar Vector DB technologies.

• Implement vector optimization strategies for high-performance semantic search and retrieval accuracy.

• Design scalable embedding pipelines using LangChain, LlamaIndex, and modern retrieval frameworks.

• Develop search boosting and ranking optimization methods to improve contextual relevance.

Graph AI & Intelligent Reasoning

• Build graph topology and layout-based AI systems for enhanced reasoning and contextual intelligence.

• Implement graph-driven retrieval architectures and knowledge graph integrations.

• Develop intelligent AI agents capable of multi-step reasoning and autonomous decision-making.

AI Infrastructure, Deployment & MLOps

• Lead AI platform deployment using cloud-native technologies on AWS, Azure, or GCP.

• Architect scalable MLOps pipelines, CI/CD workflows, and containerized AI environments using Docker and Kubernetes.

• Drive model optimization, hyperparameter tuning, inference acceleration, and scalability improvements.

• Establish governance, monitoring, observability, and evaluation frameworks for enterprise AI systems.

Leadership & Innovation

• Mentor AI engineers and data scientists on architecture best practices and emerging AI technologies.

• Collaborate with business stakeholders to define AI strategy and enterprise AI adoption.

• Stay updated with the latest advancements in Generative AI, Graph AI, Agentic Systems, Diffusion Models, and Multimodal AI research.

Required Skills & Qualifications:

Experience:

• 8+ years of experience in AI/ML development and architecture with strong focus on Generative AI and Enterprise AI Systems.

• Proven experience architecting large-scale AI platforms and production-grade AI solutions.

Technical Skills:

• Advanced Python proficiency with expertise in TensorFlow, PyTorch, Keras, and AI framework integration.

• Strong hands-on experience with:

o LLMs and transformer architectures

o RAG, Graph RAG, and Agentic RAG

o LLMWiki and knowledge-driven AI systems

o Vector DB technologies and vector optimization

o LangChain and LlamaIndex

o Diffusion Models

o Graph topology and layout-based reasoning

o Search boosting and retrieval optimization

NLP & AI Expertise:

• Deep understanding of GPT, BERT, multimodal transformers, and advanced NLP architectures.

• Experience fine-tuning LLMs and designing custom AI pipelines.

• Strong expertise in prompt engineering, Chain of Thought (CoT) reasoning, and intelligent agent orchestration.

Cloud & Infrastructure:

• Experience with AWS, Azure, or GCP for enterprise AI deployment.

• Strong knowledge of MLOps, CI/CD pipelines, Docker, Kubernetes, and scalable distributed systems.

Soft Skills:

• Strong leadership and architectural decision-making capabilities.

• Excellent analytical, problem-solving, and communication skills.

• Ability to collaborate across engineering, research, and business teams.

Preferred Skills:

• Experience building enterprise-grade AI copilots and autonomous AI agents.

• Research exposure in Graph AI, Agentic AI, Multimodal Systems, or Diffusion Models.

• Knowledge of AI evaluation frameworks, explainability, and interpretability techniques.

• Experience with synthetic data generation and large-scale semantic search systems.

• Contributions to open-source AI frameworks or research publications will be an added advantage.