AI Architect

Job Summary

We are currently seeking a AI Architect to join our team in Noida / Gurgaon, Delhi (IN-DL), India (IN).

Responsibilities

• 12+ years of experience in software engineering, enterprise architecture, solution architecture, platform architecture, or senior technical leadership roles.
• Strong cumulative technical knowledge across AI/ML, LLMs, agentic systems, software engineering, cloud platforms, distributed systems, data architecture, APIs, DevOps, and security.
• Strong hands-on understanding of Python for AI engineering, automation, orchestration, and AI service development.
• Strong hands-on understanding of C#, .NET and enterprise backend application architecture.
• Strong SQL expertise and understanding of relational databases, data modeling, query optimization, and enterprise data access patterns.
• Proven experience designing enterprise-scale platforms or applications in complex, data-intensive environments.
• Experience architecting LLM-based applications, AI agents, RAG systems, workflow automation, and intelligent decision-support solutions.
• Experience with agentic AI frameworks such as LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, Google ADK, or similar frameworks.
• Strong understanding of MCP server architecture and how AI systems integrate with enterprise APIs, tools, repositories, and data platforms.
• Experience with cloud-native architecture on AWS, Azure, or Google Cloud.
• Strong knowledge of microservices, APIs, event-driven architecture, containers, CI/CD, infrastructure-as-code, observability, and production operations.

Preferred Skills

• Experience in financial services, capital markets, ratings, risk analytics, commodities, fintech, or regulated enterprise environments.
• Experience with AWS services such as EC2, ECS, Lambda, RDS, API Gateway, SageMaker, Bedrock, CloudFormation, CDK, or comparable cloud services.
• Experience with vector databases such as OpenSearch, FAISS, Pinecone, or pgvector.
• Experience with AI governance, model lifecycle management, responsible AI, model risk controls, data privacy, and auditability.
• Experience supporting SaaS modernization, platform transformation, operating model transformation, or enterprise architecture governance.