AI Solutions Architect

Nuaav; Dadri; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Nuaav is seeking an AI Architect to own enterprise AI platform architecture across the Product Development Lifecycle. You will design multi-agent systems for requirements engineering, product management, software development, code review, testing, DevSecOps, and release engineering.

You will build reusable AI services, APIs, SDKs, and agent frameworks, define LLM orchestration, governance, and model-routing strategies, and collaborate with Product, Engineering and Security teams to set

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Over 10 years of data engineering experience with leadership exposure.
• Over 4 years building AI/ML or GenAI solutions.
• Strong knowledge of LLMs, RAG, agentic AI, MCP, vector databases, and AI evaluation.
• Hands-on experience with major cloud AI platforms (Azure OpenAI, AWS Bedrock, Google Vertex AI).
• Strong experience with Kubernetes, Docker, and cloud-native architectures.
• Familiarity with agent frameworks (LangGraph, Semantic Kernel, AutoGen, CrewAI, Microsoft Agent Framework).
• Experience with Claude ecosystem and Anthropic API, plus Python backend development with FastAPI.

Responsibilities

• Define enterprise AI platform architecture supporting the full Product Development Lifecycle.
• Design multi-agent systems for requirements engineering, product management, software development, and release engineering.
• Build reusable AI services, APIs, SDKs, and agent frameworks; architect RAG, knowledge graphs, and memory layers.
• Establish LLM orchestration and model-routing strategies; govern security, responsible AI, and prompt management.
• Lead governance involving security, guardrails, evaluation frameworks, and human-in-the-loop processes.
• Collaborate with Product, Engineering, Security, and Enterprise Architecture to evaluate emerging AI technologies.

Skills

Leadership

Cross-functional collaboration

Architectural thinking

Communication

Strategic planning

Education

Bachelor's or Master's in CS/Engineering

Tools

Kubernetes

Docker

Azure/OpenAI/AWS Vertex AI (cloud platforms)

LangGraph

Semantic Kernel

AutoGen

CrewAI

Claude ecosystem

Anthropic API

FastAPI

Job description

The ideal candidate will be responsible for working cross-functionally to understand architecture needs by multiple business units. To be effective in this position, you must feel comfortable owning the entire architecture development process from inception to completion.

Responsibilities

As AI Architect, you will define the enterprise AI platform architecture supporting the full Product Development Lifecycle and design multi-agent systems for requirements engineering, product management, software development, code review, testing, DevSecOps, documentation, and release engineering. You will build reusable AI services, APIs, SDKs, and agent frameworks; architect RAG, knowledge graph, memory, and context-management layers; and establish LLM orchestration and model-routing strategies.

You will lead AI governance across security, responsible AI, guardrails, prompt management, evaluation frameworks, and human-in-the-loop processes. Partnering with Product, Engineering, Security, and Enterprise Architecture teams, you will evaluate emerging AI technologies and define enterprise standards.

Hands-on responsibilities include designing and deploying Claude-native agents and subagents using Claude Code, Skills (SKILL.md), and project rules (CLAUDE.md); building MCP servers and FastAPI endpoints that expose internal tools and data as agent-callable services; and implementing multi-agent orchestration patterns such as supervisor/worker, planner/executor, reflection, and handoff across the platform.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• Over 10 years of data engineering experience that includes significant team leadership or management exposure
• Over 4 years building AI/ML or GenAI solutions.
• Should have strong knowledge of LLMs, RAG, agentic AI, MCP, vector databases, and AI evaluation.
• Hands-on experience across at least one major cloud AI platform such as Azure AI Foundry, Azure OpenAI, AWS Bedrock, or Google Vertex AI.
• Strong experience with Kubernetes, Docker, and cloud-native architectures.
• Familiarity with agent frameworks such as LangGraph, Semantic Kernel, AutoGen, CrewAI, or the Microsoft Agent Framework.
• Strong grounding in API architecture and in integrating AI into enterprise SDLC platforms.
• Hands-on experience with the Claude ecosystem
• Production experience with the Anthropic API — including tool use, structured outputs, streaming, and prompt caching — as well as strong Python skills, covering backend API development with FastAPI (or Starlette/Flask), async patterns, REST design, authentication, and API contracts that double as agent tools.