Gurugram | 08/Jul/2026

About the job

We are looking for an experienced Solution Architect to lead the design and implementation of enterprise-grade Agentic AI platforms powered by Large Language Models (LLMs). The ideal candidate will have a strong software engineering background with extensive architecture experience in designing scalable, secure, and production-ready AI solutions. You will be responsible for architecting multi-agent AI systems, integrating AI capabilities with enterprise applications, establishing engineering standards, and driving end-to-end solution delivery for large-scale enterprise customers. This role requires expertise in modern AI frameworks, cloud-native architecture, enterprise integrations, and stakeholder management while mentoring engineering teams and influencing strategic technology decisions.

Responsibilties

- Enterprise AI Architecture: Design and architect enterprise-scale multi-agent AI platforms capable of supporting production workloads.
- Define architecture for agent orchestration inter-agent communication memory management tool calling planning and autonomous workflows.
- Design reusable AI frameworks, SDKs, templates, and reference architectures to accelerate solution delivery.
- AI Engineering & Agentic AI: Build foundational AI agents and reusable components using modern Agentic AI frameworks.
- Architect Retrieval-Augmented Generation (RAG) solutions for enterprise knowledge management.
- Design prompt engineering strategies structured output's tool/function calling and workflow orchestration.
- Define evaluation frameworks for LLM quality, accuracy, and safety.
- Enterprise Integrations:



Design secure integrations with enterprise platforms including Salesforce Microsoft Dynamics SAP ServiceNow CRM Platforms ERP Systems ITSM Platforms using: REST APIs Event-driven architectures Model Context Protocol (MCP) Enterprise SDKs Custom Connectors Platform.
- Security & Governance Design enterprise AI platforms with emphasis on: Multi-tenancy Identity & Access Management LLM Guardrails Prompt Injection Protection PII Detection & Masking Data Governance Agent Monitoring Audit Logging Observability Reliability Compliance with enterprise security standards Cloud Architecture.
- Design highly available AI platforms on AWS and/or Azure using: Containers Kubernetes Serverless Computing Event-driven Architectures Infrastructure as Code (Terraform/CloudFormation/Bicep) Vector Databases Leadership & Stakeholder Management.
- Define engineering standards, architecture principles, coding guidelines, and best practices.
- Mentor AI engineers and conduct architecture and code reviews. Collaborate with business stakeholders, project managers, and client leadership to convert business problems into AI-driven solutions.
- Lead solution estimation, technical planning, risk assessment, and architecture governance..

Required Qualification

- 12+ years of software engineering experience with progression into architecture roles.
- Proven experience delivering at least one production-grade enterprise multi-agent AI platform.
- Minimum 3 years of hands-on experience with Generative AI and Large Language Models.




- Strong experience designing secure, scalable, cloud-native AI solutions.
- Experience integrating enterprise applications such as Salesforce SAP Microsoft Dynamics ServiceNow and other enterprise systems.
- Solid communication, consulting, stakeholder management, and leadership skills.
- Programming: Python (Mandatory) TypeScript / Node.js (Preferred) Generative AI Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Prompt Engineering Structured Outputs Tool Calling Multi-model Integration.
- Agentic AI Frameworks: Hands-on experience with one or more LangGraph CrewAI AutoGen OpenAI Agents SDK Amazon Bedrock Agents Semantic Kernel.
- AI Architecture: Multi-Agent Orchestration Agent Communication Memory Management State Management Human-in-the-Loop Workflows AI Evaluation Frameworks Enterprise Integration REST APIs Model Context Protocol (MCP) API Gateways Event Streaming Enterprise Messaging Cloud Platforms: AWS Azure Experience with: Containers Kubernetes Serverless Computing.
- Infrastructure as Code Vector Databases Software Engineering.
- CI/CD Automated Testing Design Patterns Microservices.
- Distributed Systems Enterprise Architecture Strong understanding of: Scalability High Availability Disaster Recovery (DR) Business Continuity Planning (BCP) Zero Trust Architecture OWASP Top 10 OWASP LLM Top 10..

Skills

Python (Mandatory) TypeScript / Node.js (Preferred).

Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Prompt Engineering.

LangGraph CrewAI AutoGen OpenAI Agents SDK Amazon Bedrock Agents Semantic Kernel.

Multi-Agent Orchestration Agent Communication Memory Management.

Gurugram , Hybrid | Contract

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