Principal AI Architect – GenAI, LLMs - Dubai
2 days ago
Job description
Qualifications & Experience
- 8+ years of total experience, with 4+ years in AI/ML Engineering roles.
- Demonstrated experience leading end-to-end AI/ML solution design and production deployment.
- Proven track record in Generative AI, LLMs, NLP, and AI agent development.
- Expert in Python and familiar with modern ML/NLP frameworks: HuggingFace, LangChain, PyTorch, TensorFlow, etc.
- Experience fine-tuning LLMs for domain-specific applications (e.g., Q&A systems, auto-documentation, predictive insights).
- Hands-on experience building, scaling, and optimizing AI systems on OCI, with knowledge of hybrid/multi-cloud architectures.
- Strong knowledge of machine learning algorithms, prompt engineering, vector databases, and RAG pipelines.
- Familiar with MLOps, model governance, and CI/CD for ML workflows.
Key Responsibilities
- Architect, build, and deploy production-grade AI/ML models with a strong focus on GenAI, LLMs, and intelligent agents.
- Serve as a lead architect across multiple cross-functional teams delivering AI-enabled applications.
- Design scalable, cloud-native AI solutions using Oracle Cloud Infrastructure (OCI) and other multi-cloud platforms.
- Mentor teams on solution design, best practices, and delivery excellence for AI projects.
- Guide enterprise-wide AI architecture strategy, ensuring alignment with data strategy, DevOps, and security best practices.
- Engage with C-suite stakeholders to define AI priorities, value propositions, and roadmaps.
- Lead solution estimation, technical governance, and program oversight.
- Contribute to GTM initiatives, including customer-facing demos and proposal development.
- Stay current with the latest advancements in GenAI, LLM optimization, AI agent architectures, and model integration strategies.
Publish internal whitepapers, present at leadership forums, and help grow the AI practice through coaching and community engagement.
Core Competencies & Technical Expertise
- Enterprise Architecture & AI Strategy
- Application Development (with focus on integrating AI into existing stacks)
- Multi-cloud & Distributed Architecture (OCI expertise is a must; experience with AWS, Azure, or GCP also valuable)
- AI/ML Security & Compliance
- DevOps & Agile AI Delivery
- Integration & Data Engineering Strategy
- Stakeholder Engagement – including Executive Leadership
- Program Oversight & Governance
- Solution Design, Proposals, and Estimates
- Industry Vertical: Proficiency in at least one Industry vertical will be an added advantage.
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