AI Solution Architect (Azure Pre-sales)

Virtua Advanced Solution; Dubai; On-site; AED 400,000 - 650,000; Full time

Job summary

Virtua Advanced Solution in the United Arab Emirates is seeking a senior AI/Cloud Architect to lead discovery, translate business priorities into scalable, secure generative AI solutions, and design enterprise architectures on the Microsoft cloud stack.

You will own the technical workstream for RFPs/RFIs, assess model and platform trade-offs, and present results in workshops, reviews and bid presentations to executive stakeholders.

Qualifications

• 7+ years across software engineering, cloud architecture, AI/ML engineering.
• At least 3 years designing generative AI solutions with LLMs and enterprise RAG/agents.
• Proven delivery of AI solutions beyond PoC with production‑grade practices.
• Strong Python and APIs/SDKs; C#/.NET advantageous.
• Deep understanding of LLM patterns: prompt engineering, embeddings, retrieval, orchestration.
• Experience integrating AI with enterprise apps, APIs and identity platforms.

Responsibilities

• Lead technical discovery with client stakeholders to translate priorities into AI use cases and delivery approach.
• Design secure, scalable architectures for generative AI and agentic AI on the Microsoft cloud stack.
• Build demos, accelerators and PoCs with production‑relevant patterns.
• Own the RFP/RFI technical workstreams: scope, assumptions, BOM, delivery risks.
• Define grounding, memory orchestration, observability and human‑in‑the‑loop patterns for each use case.
• Present solutions in workshops and bid presentations; respond to enterprise questions.
• Shape opportunities with delivery teams; identify reusable assets; avoid overcommitment.
• Support due diligence and handover ensuring traceability into delivery.
• Maintain knowledge of Microsoft AI services and licensing; turn into reusable assets.

Skills

Python development

APIs/SDKs

LLM patterns

Prompt engineering

Agent orchestration

Communication

Tools

Azure AI

Job description

Key Responsibilities

Lead technical discovery with client business data security and technology stakeholders convert business priorities into qualified AI use cases solution requirements and a practical delivery approach Design secure scalable enterprise architectures for generative AI agentic AI conversational AI intelligent search document intelligence and AI-enabled applications using the Microsoft cloud stack Build working demonstrations accelerators and proof-of-concepts using production-relevant patterns not only mock-ups to validate feasibility user experience integration and expected value Own the technical workstream of RFPs RFIs and proposals including architecture solution narrative scope assumptions dependencies non-functional requirements effort estimates bill of materials and delivery risks Define RAG grounding tool-use memory orchestration evaluation observability and human-in-the-loop patterns appropriate to each use case Assess model and platform choices across quality latency throughput security data residency responsible AI and cost explain the trade-offs clearly to both technical and executive audiences Present solutions in workshops solution reviews demonstrations and bid presentations respond credibly to detailed questions from enterprise architecture cybersecurity and procurement teams Work with account industry and delivery teams to shape opportunities identify reusable assets and position differentiators without overcommitting scope or capability Support technical due diligence implementation planning and handover after award ensuring that proposal commitments are understood feasible and traceable into delivery Maintain current knowledge of Microsoft AI services reference architectures licensing and emerging agentic patterns and turn that knowledge into reusable pre-sales assets

Qualifications

7+ years of professional experience across software engineering, cloud architecture, AI/ML engineering or enterprise solution consulting. At least 3 years of hands‑on experience specifically designing and building generative AI solutions using large language models, including enterprise RAG and/or AI agents. Demonstrable experience delivering AI or advanced analytics solutions beyond proof‑of‑concept stage, with a strong understanding of production engineering, security, monitoring and operational support. Strong hands‑on development capability in Python and APIs/SDKs; experience with C#/.NET is advantageous. Deep understanding of LLM application patterns: prompt and context engineering, embeddings, vector and hybrid retrieval, tool/function calling, structured outputs, agent orchestration, evaluation and guardrails. Experience integrating AI solutions with enterprise applications, APIs, databases, document repositories and identity platforms. Strong knowledge of cloud security, Entra ID, managed identities, private networking, secrets management, role‑based access control, data privacy and responsible AI controls. Proven client‑facing experience in discovery, solution presentations, technical writing, estimation and proposal development for complex enterprise opportunities. Ability to produce clear architecture diagrams, sequence flows, assumptions, sizing models and implementation plans under bid deadlines. Excellent written and verbal English; able to challenge requirements constructively and communicate complex concepts without unnecessary jargon.