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AI Architect

Job Description - AI Architect

Description

Qualifications & Experience



  • 12–15 years of total experience, with 5+ years in Data Science or 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.

  • Strong communication and stakeholder management skills—able to bridge the gap between technical and executive teams.



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.


Qualifications

Career Level - N/A



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