AI Architect – GenAI, LLMs & AI Agents

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.

Responsibilities

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.

Qualifications

Career Level - IC4

Required Experience:

Unclear Seniority