AI Architect (Generative AI & Graph Technologies)

Role & responsibilities

We are seeking an 10+ years of experienced AI Architect to lead the design, development, and implementation of enterprise-scale AI solutions. The ideal candidate will possess deep expertise in Generative AI, Large Language Models (LLMs), Graph Technologies, and modern application architecture. This role requires driving end-to-end AI solution architecture, from requirement analysis and system design to deployment, scalability, security, and governance.

The candidate will work closely with business stakeholders, product teams, data scientists, and engineering teams to build intelligent, scalable, and production-ready AI systems.

Mandatory Technical Skills

Generative AI & LLM Ecosystem

• Hands-on experience with:
• OpenAI Models
• LangChain
• LangGraph
• Retrieval Augmented Generation (RAG) Pipelines
• Prompt Engineering
• AI Agents and Multi-Agent Systems
• Vector Databases (Pinecone, ChromaDB, Weaviate, Milvus, FAISS, etc.)

Graph Ecosystem

• Experience with Graph Databases and Knowledge Graphs
• Neo4j or equivalent graph technologies
• Graph-based data modeling and relationship management
• Graph-powered retrieval and reasoning architectures

Programming & Data Technologies

• Strong proficiency in:
• Python
• SQL
• Experience developing scalable backend services and AI integrations

Application Architecture

• REST APIs
• GraphQL
• Authentication & Authorization frameworks
• Microservices Architecture
• Scalable and Secure Application Design
• Enterprise Integration Patterns

Key Responsibilities

• Define and own the AI architecture strategy for enterprise-grade GenAI solutions.
• Design and implement scalable LLM-based applications leveraging RAG and Agentic AI frameworks.
• Architect knowledge graph and graph-enhanced AI solutions for complex business use cases.
• Lead the selection and implementation of vector databases and retrieval strategies.
• Design secure, resilient, and high-performing AI applications.
• Establish AI governance, observability, security, and model evaluation frameworks.
• Collaborate with cross-functional teams to translate business requirements into technical solutions.
• Guide development teams on architecture best practices, coding standards, and deployment strategies.
• Drive solution optimization, scalability, and performance improvements.
• Mentor engineers and provide technical leadership across AI initiatives.

Required Qualifications

• 10+ years of overall software engineering and architecture experience.
• Proven experience architecting and delivering enterprise AI/GenAI solutions in production environments.
• Deep understanding of LLM architectures, RAG frameworks, prompt engineering, and AI orchestration frameworks.
• Strong experience with graph databases, knowledge graphs, and graph-based reasoning systems.
• Expertise in designing secure, scalable, and cloud-native applications.
• Strong understanding of distributed systems and API design.
• Experience working in Agile delivery environments.
• Excellent stakeholder management, communication, and leadership skills.