The AI Solutions Architect will lead the technical design and implementation of enterprise AI solutions, including AI copilots, intelligent assistants, document intelligence platforms and AI-powered business workflows.

The role will define AI architecture standards, evaluate emerging AI technologies, establish governance practices and mentor technical teams to accelerate AI adoption across the organization.

The position requires a strong understanding of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, AI orchestration frameworks and enterprise system integration. The ideal candidate should be a hands-on professional capable of designing and delivering AI solutions while collaborating effectively with cross-functional teams. Job Summary

The AI Solutions Architect will be responsible for designing, developing and implementing Generative AI and Agentic AI solutions that drive business transformation, operational efficiency, and innovation across the organization. The role will bridge business requirements and technical implementation by working closely with Data Scientists, Software Development teams and business stakeholders to deliver scalable, secure and production-ready AI solutions.

Key Roles and Responsibilities:

AI Solution Architecture

Design scalable Generative AI and Agentic AI solutions aligned with business objectives.
Define AI architecture standards, design principles, and implementation frameworks.
Evaluate and recommend AI technologies, platforms, and tools based on business needs.

Generative AI Development

Design and implement AI copilots, enterprise knowledge assistants, and document intelligence solutions.
Develop Retrieval-Augmented Generation (RAG) solutions using enterprise knowledge sources.
Build prompt engineering, evaluation, and optimization frameworks for AI applications.

Agentic AI Development

Design and develop AI agents capable of autonomous task execution.
Build multi-agent workflows and orchestration solutions.
Integrate AI agents with enterprise applications, APIs, and business processes.

AI Governance & Best Practices

Establish AI development standards, governance frameworks, and security guidelines.
Ensure AI solutions are scalable, reliable, secure, and maintainable.
Promote responsible AI practices across projects.

Technical Leadership

Mentor and provide technical guidance to Data Scientists and Development teams.
Conduct architecture and design reviews.
Encourage knowledge sharing and AI capability development within the Digital Innovation team.

Business Collaboration

Collaborate with business stakeholders to identify high-value AI use cases.
Translate business challenges into AI-enabled solutions.
Support digital transformation initiatives through AI-driven innovation.

Continuous Innovation

Stay updated on advancements in Generative AI, Agentic AI, automation, and emerging technologies.
Evaluate new frameworks, tools, and platforms to enhance organizational AI capabilities.

Qualifications and Experience Required:

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Information Technology, Data Science, or a related discipline.
5 to 8 years of overall software development or AI experience.
Minimum 2–3 years of hands-on experience in designing and implementing Generative AI solutions.
Experience in developing and deploying production-ready AI applications.
Experience working with cross-functional teams and enterprise software environments.

Technical Skills

Strong proficiency in Python.
Experience with OpenAI, Azure OpenAI, Gemini, Claude or similar LLM platforms.
Hands-on experience with LangChain, LangGraph, CrewAI, LlamaIndex or equivalent AI orchestration frameworks.
Experience implementing Retrieval-Augmented Generation (RAG) solutions.
Knowledge of vector databases and embeddings.
Experience integrating AI solutions using REST APIs and enterprise applications.
Familiarity with cloud platforms such as AWS or Azure is desirable.

Preferred Skills

Experience in workflow automation and enterprise integrations.
Understanding of MLOps/LLMOps concepts.
Knowledge of the Architecture, Engineering, Construction, and Operations (AECO) domain will be an added advantage.

Competencies

Strong analytical and problem-solving skills.
Excellent communication and stakeholder management abilities.
Ability to translate business requirements into scalable AI solutions.
Leadership and mentoring capabilities.
Passion for innovation and continuous learning.

Compensation:

The selected candidate will receive competitive compensation and remuneration policies in line with qualifications and experience. Compensation will not be a constraint for the right candidate.

What We Offer:

A fulfilling working environment that is respectful and ethical
A stable and progressive career opportunity
State-of-the-art office infrastructure with the latest hardware and software for professional growth
In-house, internationally certified training division and innovation team focusing on training and learning the latest tools and trends.
Culture of discussing and implementing a planned career growth path with team leaders
Transparent fixed and variable compensation policies based on team and individual performances, ensuring a productive association.

AI Solutions Architect

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