AI/ML Architect

TuTeck Technologies; Kolkata District; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

TuTeck Technologies seeks an AI/ML Enterprise Architect to define scalable enterprise architectures and technology strategy for AI-enabled business solutions. You will design GenAI, AI/ML, and agentic AI solutions across cloud and hybrid environments, with hands-on exposure to A2A and MCP and experience building AI-powered assistants and chatbots.

The role requires leading architectural decisions, evaluating models and frameworks, and collaborating with security, data, and business teams to

Qualifications

• 8–12 years in software/solution/enterprise architecture roles.
• Strong AI/ML and Generative AI architecture experience.
• Experience with enterprise integration, APIs, microservices and event-driven patterns.
• Hands-on with A2A and MCP for AI agents and ecosystems.
• Knowledge of Azure AI services, cloud architecture, and cloud-native tech.
• Experience with AI/agent frameworks, LLM apps, RAG, tool calling, and orchestration.

Responsibilities

• Define enterprise AI/ML architecture, strategy, and reference architectures.
• Design scalable, secure GenAI and agentic AI solutions for enterprise use cases.
• Architect integrations across apps, APIs, data platforms, AI services, and third‑party systems.
• Create A2A/MCP-based architectures for AI agents and ecosystems.
• Evaluate AI models, frameworks, cloud services, APIs, and vector databases.
• Leverage Azure AI services to build enterprise-grade AI solutions.
• Define patterns for chatbots, virtual assistants, AI agents, and RAG apps.
• Ensure security, governance, observability, and compliance in architectures.
• Collaborate with engineering, product, security, data, and business teams.
• Perform architecture reviews and guide development teams.

Skills

AI/ML Architecture

Generative AI

Azure cloud architecture

APIs & microservices

Security

A2A MCP exposure

LLM-based apps

Chatbots/Agents

Stakeholder management

Cloud services

Tools

Azure

Docker

Kubernetes

LangChain

API Management

Job description

AI/ML Enterprise Architect

Experience: 8–12 Years

Location: Delhi/Kolkata

Employment Type: Full-Time

Job Summary

We are looking for an experienced AI/ML Enterprise Architect to define and drive scalable enterprise architecture and technology strategy, with strong expertise in AI/ML, Generative AI, cloud architecture, enterprise integrations, APIs, and security.

The ideal candidate will have a strong track record of designing enterprise-grade AI solutions, integrating AI capabilities with existing business applications, and making strategic architectural decisions across cloud and hybrid environments. The candidate should also have hands‑on exposure to A2A (Agent-to-Agent) communication and MCP (Model Context Protocol) and experience building or architecting AI-powered assistants, chatbots, and agentic solutions.

Key Responsibilities

• Define enterprise AI/ML architecture, technology strategy, and reference architectures aligned with business and technology objectives.
• Design scalable, secure, and highly available GenAI, AI/ML, and agentic AI solutions for enterprise use cases.
• Architect enterprise integrations across applications, APIs, data platforms, AI services, and third‑party systems.
• Design and implement A2A and MCP‑based architectures for AI agents and enterprise AI ecosystems.
• Evaluate and recommend appropriate AI models, agent frameworks, cloud services, APIs, vector databases, and integration technologies.
• Leverage Microsoft Azure AI services and other cloud‑native capabilities to build enterprise‑grade AI solutions.
• Define architecture patterns for chatbots, virtual assistants, AI agents, RAG‑based applications, and enterprise AI platforms.
• Establish architectural standards covering security, scalability, performance, reliability, observability, governance, and compliance.
• Collaborate with engineering, product, security, data, and business teams to translate requirements into scalable technical solutions.
• Conduct architecture reviews and provide technical direction to development and engineering teams.
• Assess emerging AI technologies and frameworks and recommend their adoption where they provide business value.
• Identify technical risks, architecture gaps, and integration challenges and define appropriate mitigation strategies.
• Create and maintain solution architecture documents, technical specifications, architecture diagrams, and technology roadmaps.
• Ensure AI solutions follow enterprise security and responsible AI principles.

Required Skills & Experience

• 8–12 years of overall experience in software architecture, solution architecture, enterprise architecture, or related technology roles.
• Strong experience in AI/ML and Generative AI architecture and enterprise AI solution design.
• Strong understanding of enterprise integration architecture, APIs, microservices, event‑driven architecture, and distributed systems.
• Hands‑on experience with A2A (Agent-to-Agent) and MCP (Model Context Protocol).
• Strong knowledge of Microsoft Azure AI services, Azure cloud architecture, and cloud‑native technologies.
• Experience with AI/agent frameworks, LLM‑based applications, RAG, tool calling, and agentic workflows.
• Experience designing or architecting chatbots, virtual assistants, conversational AI, or enterprise AI platforms.
• Strong understanding of API management, authentication/authorization, identity, security, and enterprise integration patterns.
• Experience with cloud platforms, preferably Microsoft Azure.
• Strong understanding of AI/ML lifecycle, model integration, deployment, monitoring, and governance.
• Strong solution design and architectural decision-making capabilities.
• Excellent understanding of scalability, high availability, performance, security, and resilience principles.
• Strong communication and stakeholder‑management skills, with the ability to explain complex technical concepts to both technical and business stakeholders.

Good to Have

• Experience with Azure OpenAI / Microsoft Foundry, Azure AI Search, Azure AI services, or equivalent AI platforms.
• Experience with LangChain, LangGraph, Semantic Kernel, AutoGen, or similar agent frameworks.
• Knowledge of RAG architectures, vector databases, embeddings, prompt engineering, and LLM orchestration.
• Experience with Docker, Kubernetes, CI/CD, and DevSecOps.
• Exposure to AI governance, responsible AI, data privacy, and enterprise security frameworks.
• Experience working with large‑scale enterprise transformation or modernization initiatives.