GenAI Solutions Architect

Deeplight; Dubai; On-site; AED 293,000 - 441,000; Full time

Job summary

A growing AI delivery company in Dubai seeks an experienced GenAI Solutions Architect to design and build LLM systems. You'll collaborate with various teams, deploy scalable solutions, and engage in hands-on execution. The role demands a strong background in Machine Learning, Python proficiency, and experience with vector databases. Benefit from a competitive salary, performance bonuses, and growth opportunities in a rapidly expanding field.

Benefits

Competitive salary and performance bonuses

Comprehensive health insurance

Professional development support

Flexible working arrangements

Career advancement opportunities

Qualifications

• Proven background in Machine Learning.
• Experience building and deploying GenAI-powered applications.
• Deep understanding of LLMs and GenAI design patterns.
• Proficiency in Python and related frameworks.
• Experience with vector databases.
• Familiarity with cloud infrastructure.

Responsibilities

• Architect end-to-end GenAI systems.
• Design and optimize RAG workflows.
• Integrate LLMs and APIs into products.
• Collaborate with cross-functional teams.
• Deploy to production following best practices.

Skills

Machine Learning

GenAI-powered applications

LLMs understanding

Python

Cloud infrastructure (AWS, GCP, Azure)

Cross-functional collaboration

Tools

LangChain

Transformers

OpenAI SDKs

vector databases (FAISS, Pinecone, Qdrant)

Job description

About the Role

We’re looking for an experienced and personable GenAI Solutions Architect to join our growing AI delivery team. You’ll design and build large language model (LLM) systems that move beyond experimentation and into real-world production - powering search, summarisation, knowledge assistants, and automation for enterprise clients.

This is a hands-on, execution-focused role that requires strong stakeholder management skills. You’ll work closely with product managers, engineers, and AI specialists to ship scalable solutions. You won’t be buried in research or building theoretical models; you’ll be deploying actual systems that users rely on every day.

Requirements

What You’ll Do

• Architect end-to-end GenAI systems, including prompt chaining, memory strategies, token budgeting, and embedding pipelines
• Design and optimize RAG (Retrieval-Augmented Generation) workflows using tools like LangChain, LlamaIndex, and vector databases (FAISS, Pinecone, Qdrant). Experience with Graph RAG architectures and proficiency in Node.js required.
• Evaluate tradeoffs between zero-shot prompting, fine-tuning, LoRA / QLoRA, and hybrid approaches, aligning solutions with user goals and constraints
• Integrate LLMs and APIs (OpenAI, Anthropic, Cohere, Hugging Face) into real-time products and services with latency, scalability, and observability in mind
• Collaborate with cross-functional teams—translating complex GenAI architectures into stable, maintainable features that support product delivery
• Write and review technical design documents and remain actively involved in implementation decisions
• Deploy to production with industry best practices around version control, API lifecycle management, and monitoring (e.g., hallucination detection, prompt drift)

What You’ll Bring

• Proven background in Machine Learning
• Proven experience building and deploying GenAI-powered applications, in enterprise or regulated environments
• Deep understanding of LLMs, vector search, embeddings, and GenAI design patterns (e.g. RAG, prompt injection protection, tool use with agents)
• Proficiency in Python and fluency with frameworks and libraries like LangChain, Transformers, Hugging Face, and OpenAI SDKs
• Experience with vector databases such as FAISS, Qdrant, or Pinecone
• Familiarity with cloud infrastructure (AWS, GCP, or Azure) and core MLOps concepts (CI / CD, monitoring, containerization)
• Proven experience supporting and/or delivering AI / ML Products
• A commercial and delivery mindset— you know how to balance speed, quality, and feasibility in fast-moving projects

Nice to Have

• Experience building multi-tenant GenAI platforms
• Exposure to enterprise-grade AI governance and security standards
• Familiarity with multi-modal architectures (e.g., text + image or audio)
• Knowledge of cost-optimization strategies for LLM inference and token usage

This Role Is Not For

• ML researchers focused on academic model development without delivery / product experience
• Data scientists unfamiliar with vector search, LLM prompt engineering, or system architecture
• Engineers who haven’t shipped GenAI products into production environments

Benefits & Growth Opportunities

• Competitive salary and performance bonuses
• Comprehensive health insurance
• Professional development and certification support
• Opportunity to work on cutting-edge AI projects
• International exposure and travel opportunities
• Flexible working arrangements
• Career advancement opportunities in a rapidly growing AI company

This position offers a unique opportunity to shape the future of AI implementation while working with a talented team of professionals at the forefront of technological innovation. The successful candidate will play a crucial role in driving our company's success in delivering transformative AI solutions to our clients.