Artificial Intelligence Architect

AI Architect

Experience: 13+ Years
Location: PAN India
Employment Type: Full-Time / Permanent

Job Summary

We are looking for a highly experienced AI Architect with 15+ years of overall technology experience and at least 5+ years in architecture leadership roles. The ideal candidate will have strong expertise in designing and delivering enterprise-scale AI solutions using Azure AI services, Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) architectures.

The candidate will be responsible for driving AI solutions from ideation, architecture, PoC, pilot, and implementation through production deployment and scale-out. This role also requires strong experience in performance engineering, technical leadership, customer-facing solutioning, RFP/RFI responses, and pre-sales activities.

Key Responsibilities

Architecture & Technical Leadership

• Own the end-to-end architecture of AI and Generative AI solutions from discovery through production implementation.
• Drive use-case identification, solution design, PoC development, pilot execution, production hardening, and scalability.
• Define reference architectures for:
• RAG solutions
• LLM applications
• AI Agents
• Multi-model pipelines
• Enterprise Generative AI applications
• Design RAG architectures covering retrievers, vector indexes, chunking strategies, embeddings, ranking, orchestration, and grounding.
• Provide technical leadership across application, data, AI/ML, platform, security, and DevOps teams.
• Lead architecture and design reviews, threat modelling, and governance activities.
• Define best practices for reliability, scalability, security, performance, and cost optimization.
• Mentor engineers and architects and develop reusable frameworks, accelerators, libraries, and reference patterns.

Azure AI Solutioning & Delivery

• Architect and implement solutions using:
• Azure OpenAI Service
• Azure AI Search
• Azure AI Foundry
• Azure Machine Learning
• Azure Cognitive Services
• Prompt Flow
• Semantic Kernel
• Design solutions using vector search, hybrid retrieval, custom scoring, reranking, and grounding techniques.
• Develop and architect LLM-based applications involving prompt engineering, orchestration, tool usage, and multi-model workflows.
• Integrate AI solutions with Azure services including:
• Azure Functions
• Azure App Service
• AKS
• Event Hub
• Azure Service Bus
• Cosmos DB
• Azure SQL Database
• Key Vault
• Private Endpoints
• Virtual Networks
• Azure API Management
• Translate business requirements into technical architecture, solution blueprints, epics, backlogs, and non-functional requirements.
• Create operational runbooks and deployment strategies for enterprise AI solutions.
• Implement Responsible AI guardrails, content filtering, safety policies, data privacy, and compliance requirements.
• Act as the primary technical and architectural contact for customers, product teams, and delivery leadership.

Performance Engineering

• Lead performance tuning and optimization of AI and LLM-based applications.
• Perform load testing, profiling, and performance analysis.
• Optimize token usage and model consumption.
• Implement caching strategies and autoscaling mechanisms.
• Define appropriate GPU and CPU sizing strategies.
• Establish telemetry, monitoring, and observability for AI applications.
• Optimize solutions for performance, reliability, scalability, and cost efficiency.

RFP & Pre-Sales Responsibilities

• Lead and contribute to RFPs and RFIs.
• Define technical solution approaches and architecture.
• Create architecture diagrams and solution documentation.
• Prepare delivery plans, effort estimations, and cost estimates.
• Develop BoQ/BoM, assumptions, risks, and technical dependencies.
• Support proposal development and define win themes and differentiators.
• Conduct customer ideation workshops and discovery sessions.
• Participate in executive briefings and customer presentations.
• Develop compelling AI solution value propositions aligned with business outcomes.

Mandatory Skills

• 15+ years of overall experience in Software Engineering, Solution Engineering, or Technology.
• Minimum 5+ years of experience in an Architect, Lead Architect, Principal Architect, or similar leadership role.
• Strong experience designing and implementing enterprise-scale AI solutions.
• Deep expertise in:
• Generative AI
• Large Language Models (LLMs)
• RAG Architectures
• Prompt Engineering
• AI Agents
• Model Orchestration
• Grounding and Tool Usage
• Strong hands-on experience with Azure AI services:
• Azure OpenAI Service
• Azure AI Search
• Azure AI Foundry
• Azure Machine Learning
• Azure Cognitive Services
• Strong understanding of vector search, hybrid search, embeddings, chunking, ranking, and reranking.
• Experience with Prompt Flow and/or Semantic Kernel.
• Strong performance engineering and optimization skills.
• Experience in RFP/RFI solutioning and pre-sales activities.
• Strong customer-facing and stakeholder management skills.

Microsoft Technology Skills

• .NET / C#
• ASP.NET Core
• Azure PaaS Services
• Azure Functions
• Azure App Service
• AKS
• SQL Server
• Cosmos DB
• Azure API Management
• Event Hub
• Service Bus
• GitHub
• Azure DevOps
• Power Platform
• Microsoft 365

Security & Governance

• Strong understanding of:
• Microsoft Entra ID
• Azure Virtual Networks
• Private Endpoints
• Azure Key Vault
• Encryption
• Data Privacy
• Data Governance
• Responsible AI
• Experience with AI governance, MLOps, and AIOps practices.
• Experience implementing security, compliance, and Responsible AI guardrails for enterprise applications.

Preferred Candidate Profile

• Strong architecture and solution design capabilities.
• Proven experience taking AI solutions from ideation to enterprise production.
• Ability to lead multiple cross-functional technical teams.
• Strong problem-solving and decision-making abilities.
• Excellent communication, presentation, and documentation skills.
• Strong customer-facing and consulting experience.
• Ability to communicate complex AI concepts to both technical and business stakeholders.