TuTeck Technologies
Website:
tutecktechnologies.com
Job details:
AI Agent Integration & Architecture Lead
Experience: 6–8 Years
Location: Remote
Department: Technology / AI & Digital Engineering
Job Overview
We are looking for an experienced AI Agent Integration & Architecture Lead to drive the design and implementation of enterprise-grade integrations across chatbot, AI agent, and intelligent automation platforms. The ideal candidate will have strong expertise in AI/GenAI architecture, enterprise integration, agent interoperability, A2A, MCP, APIs, and cloud technologies, with the ability to translate business requirements into scalable and secure technical solutions.
The candidate will provide technical leadership across architecture, solution design, integration patterns, and implementation of AI agent ecosystems.
Key Responsibilities
- Define and drive the integration strategy and architecture for enterprise AI agent ecosystems.
- Design scalable and secure solutions using A2A (Agent-to-Agent) and MCP (Model Context Protocol) integration patterns.
- Architect interoperability between enterprise chatbots, AI agents, APIs, tools, data sources, and business applications.
- Evaluate different architectural approaches and recommend the most suitable solution based on scalability, security, performance, maintainability, and business requirements.
- Design agent orchestration, context exchange, tool invocation, and communication patterns across AI platforms.
- Provide technical leadership and architectural guidance to development and delivery teams.
- Work closely with business stakeholders, product teams, engineering teams, and enterprise architects to understand requirements and define technical solutions.
- Establish best practices, design standards, reusable integration patterns, and governance frameworks for AI agent implementations.
- Ensure AI solutions comply with enterprise requirements related to security, privacy, authentication, authorization, observability, and data governance.
- Review technical designs, proof-of-concepts, and implementation approaches developed by engineering teams.
- Troubleshoot complex integration and interoperability challenges across AI and enterprise platforms.
- Support the team in evaluating emerging AI agent technologies, frameworks, protocols, and architectural patterns.
- Contribute to technical documentation, architecture diagrams, solution blueprints, and Architecture Decision Records (ADRs).
Required Skills & Experience
- 6–8 years of overall experience in software architecture, enterprise integration, AI/GenAI, or related technology domains.
- Strong hands-on experience in AI/GenAI architecture and enterprise AI integrations.
- Practical experience with A2A and MCP integration patterns and concepts.
- Strong understanding of AI agents, agent orchestration, interoperability, context exchange, tool calling, and multi-agent architectures.
- Experience with Azure AI services and Microsoft Azure cloud architecture.
- Strong knowledge of REST APIs, API gateways, authentication/authorization, webhooks, event-driven architecture, and enterprise integration patterns.
- Experience with AI/agent frameworks such as Microsoft Agent Framework, Semantic Kernel, LangChain, LangGraph, or equivalent frameworks.
- Experience working with chatbots, virtual assistants, conversational AI, or enterprise AI platforms.
- Strong understanding of LLMs, RAG, vector databases, embeddings, prompt engineering, and AI application architecture.
- Knowledge of cloud-native architecture, microservices, containers, and scalable distributed systems.
- Strong solution-design and architectural decision-making capabilities.
- Experience with security considerations for enterprise AI systems, including identity, access control, data protection, and secure tool/agent communication.
- Strong communication, stakeholder-management, and technical leadership skills.
Preferred / Good-to-Have Skills
- Experience integrating AI agents with enterprise applications such as CRM, ERP, ITSM, knowledge management, or workflow platforms.
- Experience with Azure OpenAI / Azure AI Foundry and related Azure AI capabilities.
- Knowledge of event-driven architectures, messaging platforms, and asynchronous agent communication.
- Experience with Docker, Kubernetes, CI/CD, API Management, and cloud observability.
- Familiarity with AI governance, responsible AI, and enterprise security frameworks.
- Experience leading AI architecture initiatives or technical delivery teams.
Key Competencies
- AI & GenAI Architecture
- AI Agent Integration
- A2A & MCP
- Agent Interoperability & Orchestration
- Azure AI & Cloud Architecture
- Enterprise API Integration
- Solution Architecture & Design
- Security & Scalability
- Technical Leadership
- Stakeholder Management
What We Are Looking For
The ideal candidate should be a hands-on technology leader who can bridge the gap between AI strategy and implementation. The person should be comfortable evaluating emerging agent technologies, defining architecture and integration patterns, and guiding engineering teams to deliver secure, scalable, maintainable, and enterprise-ready AI agent solutions.
Click on Apply to know more.
