AI Solution Architect

VGreen Technology Solutions (VGreenTEK); Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

VGreen Technology Solutions (VGreenTEK) Bengaluru invites an experienced AI Solution Architect to lead hands-on design, development, and deployment of production AI applications for enterprise customers. This role requires collaboration with business stakeholders and engineering teams to translate requirements into scalable architectures and govern AI initiatives end-to-end.

The ideal candidate has delivered at least one complete AI project from concept to production, with strong leadership and

Qualifications

• Hands-on implementation experience delivering production AI solutions.
• Delivered at least one end-to-end AI solution from architecture through deployment.
• Able to translate business requirements into scalable AI architectures.
• Strong customer-facing and stakeholder management experience.

Responsibilities

• Design, architect, and hands-on develop enterprise AI solutions.
• Translate business requirements into scalable AI architectures.
• Build AI applications using LLMs, RAG, AI Agents, and orchestration frameworks.
• Design and implement Knowledge Stores, Context Stores, and AI orchestration workflows.
• Develop and optimize prompts for enterprise AI use cases.
• Implement deterministic and non-deterministic AI workflows.
• Integrate AI solutions with enterprise applications and cloud platforms.
• Establish AI governance, security, guardrails, and risk controls.
• Provide technical leadership while remaining actively involved in implementation.

Skills

Hands-on AI development

Customer-facing / stakeholder mgmt

End-to-end AI project delivery

Production AI deployment

Architectural design of AI systems

Collaboration with business and eng.

LLMs, RAG, AI Agents experience

Tools

Cursor

GitHub Copilot

Claude Code

Windsurf

Gemini Code Assist

Job description

AI Solution Architect

Experience: 10+ Years

We are looking for a hands‑on AI Solution Architect with extensive experience in designing, building, and deploying enterprise-grade AI solutions. This is a customer‑facing role requiring close collaboration with business stakeholders and engineering teams to architect, develop, and implement production‑ready AI applications.

The ideal candidate must have personally built and delivered at least one end‑to‑end AI solution from architecture through deployment and production support.

This is not an architecture‑only or advisory role. Candidates must have hands‑on implementation experience and be capable of independently designing, developing, integrating, and deploying enterprise AI solutions into production.

Key Responsibilities

• Design, architect, and hands‑on develop enterprise AI solutions.
• Translate business requirements into scalable AI architectures.
• Build AI applications using LLMs, RAG, AI Agents, and orchestration frameworks.
• Design and implement Knowledge Stores, Context Stores, and AI orchestration workflows.
• Develop and optimize prompts for enterprise AI use cases.
• Implement deterministic and non-deterministic AI workflows.
• Integrate AI solutions with enterprise applications and cloud platforms.
• Establish AI governance, security, guardrails, and risk controls.
• Provide technical leadership while remaining actively involved in implementation.

Skills & Experience

• Hands‑on experience with AI‑assisted development ("Vibe Coding") using tools such as Cursor, GitHub Copilot, Claude Code, Windsurf, or Gemini Code Assist.
• Experience with Model Context Protocol (MCP).
• Exposure to vector databases such as Pinecone, Weaviate, Chroma, or Azure AI Search.
• 10+ years of overall IT solution architecture experience.
• Hands‑on in designing, developing, and deploying enterprise AI solutions.
• Proven experience delivering at least one complete AI project from concept to production.
• Strong customer‑facing and stakeholder management experience.

Technical Expertise

• Vertex AI or Azure AI Foundry
• LangGraph and LangSmith
• LLM Prompt Engineering, Prompt Evaluation & Optimization
• Knowledge Stores, Context Stores, Vector Databases, and RAG
• AI Agents and Multi‑Agent Systems
• Deterministic & Non‑Deterministic AI Orchestration
• REST APIs and Enterprise System Integration

AI Governance

• Responsible AI
• AI Governance Frameworks
• AI Risk Management
• AI Guardrails
• Security, Compliance, and Model Monitoring