Senior AI Solution Architect

Job Description

Title: Senior AI Solution Architect

Company Name: Mega Consultants (BD) Ltd.

Vacancy: 10

Age: 21 to 45 years

Job Location: Japan

Salary: Negotiable

Experience:

• 1 to 2 years

• Bachelor of Science (BSc) in Computer Science & Engineering
• Master of Science (MSc) in Computer Science & Engineering

• 1 to 2 years

• Age 21 to 45 years

• 1+ years of professional experience in cloud infrastructure, AI engineering, or solution architecture roles.

• Proven, hands-on experience with the Microsoft Azure stack  — AKS, Azure OpenAI Service, AI Foundry, Fabric, AI Search, Cosmos DB, etc.

• Demonstrated experience designing and deploying AI/ML systems in production environments.

• Strong database engineering background across at least three of: Knowledge Graph, RDB, VectorDB, NoSQL, and full-text search.

• Proficiency in Python and/or Node.js for backend API and service development.

• Solid understanding of LLM fundamentals, including RAG, fine-tuning, prompt engineering, and agentic frameworks.

• Experience implementing CI/CD, IaC, and production observability practices.

• Professional Certifications Microsoft Azure certifications, such as Solutions Architect Expert, AI Engineer Associate, or equivalent credentials, are highly preferred.

• Advanced Framework Expertise Practical experience with cutting-edge, multi-agent orchestration frameworks including LangGraph, AutoGen, or Semantic Kernel.

• Compliance & Data Governance Strong familiarity with enterprise data governance, AI compliance frameworks, and responsible AI principles.

• Open-Source Deployment Prior exposure to deploying open-source Large Language Models (such as Llama, Mistral, Phi) specifically on Azure cloud infrastructure.

• Technical Industry Contributions Active contributions to open-source AI tooling, technical publications, or presentations at technical conferences.

• Collaboration & Communication Excellent cross-functional collaboration and communication skills, with a proven ability to lead technical discovery sessions and architecture reviews with stakeholders.

• Equal Opportunity Commitment Ability to work effectively in a diverse, inclusive team environment that values all individuals regardless of race, gender, nationality, disability, or background.

We are seeking a highly skilled Senior AI Solution Architect with deep, hands-on expertise across the Microsoft Azure ecosystem and modern generative AI platforms. In this role, you will act as the ultimate technical authority bridging business requirements and cutting-edge AI capabilities. You will collaborate with cross-functional teams to translate ambiguous challenges into scalable, maintainable, and secure AI solutions. Your primary mandate will be to design and deliver end-to-end intelligent systems spanning cloud infrastructure, multi-modal AI databases, LLM-integrated microservices, and production-grade DevOps pipelines — that directly power our next-generation enterprise products.

Azure Cloud Infrastructure & Platform Engineering

• Architect and manage secure, compliant, and highly scalable Azure-based cloud infrastructure aligned with enterprise standards.

• Design multi-region, high-availability, and fault-tolerant environments using Azure VNets, AKS, App Service, and Azure API Management.

• Govern cloud expenditure and optimize resource utilization using Azure Cost Management and architectural best practices.

Generative AI Microservices Development

• Design, build, and implement production-ready generative AI microservices using Azure AI Foundry, Microsoft Fabric, and Azure AI Search.

• Develop modular, containerized AI services enabling seamless integration of LLMs into business workflows.

• Evaluate and onboard emerging Azure AI services to align product roadmaps with evolving technologies.

AI Database Architecture & Engineering

• Design polyglot persistence strategies combining Knowledge Graphs (GraphDB / Neo4j), relational databases, vector stores, NoSQL databases, and full-text search engines.

• Construct and maintain high-performance vector databases (Azure AI Search, Qdrant, Weaviate) optimized for semantic retrieval.

• Implement graph-based knowledge representations for complex entity-relationship reasoning in AI pipelines.

• Define robust data modeling, advanced indexing, and query optimization strategies across heterogeneous database systems.

AI Solution Architecture & LLM Integration

• Design connection layers between LLMs (GPT-4o, Claude, Gemini, OSS models) and enterprise databases, including RAG pipelines and agentic memory systems.

• Architect and deploy AI agent platforms supporting multi-agent orchestration, tool usage, and long-horizon execution.

• Establish prompt engineering patterns, context management strategies, and LLM evaluation frameworks.

• Lead technical discovery sessions, architecture reviews, and proof-of-concept (PoC) engagements.

Backend Service & API Development

• Design and implement high-throughput RESTful and event-driven APIs connecting AI microservices, databases, and front-end systems.

• Develop resilient backend services in Python or Node.js using clean architecture and domain-driven design principles.

• Enforce API governance standards covering versioning, authentication (OAuth2/API keys), rate limiting, and observability.

DevOps & Production Environment Engineering

• Engineer and maintain automated CI/CD pipelines (Azure DevOps / GitHub Actions) for AI deployments and infrastructure changes.

• Implement Infrastructure-as-Code (IaC) using Terraform or Bicep for reproducible environments.

• Establish monitoring, alerting, and incident response workflows using Azure Monitor, Application Insights, or equivalent tools.

• Drive security-by-design across SDLC with secrets management, RBAC, and continuous vulnerability scanning.