AI Solutions Architect
Posted Updated
Description
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
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.