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Oracle · BENGALURU, KARNATAKA, India

AI Architect

BENGALURU, KARNATAKA, IndiaOperations

Listed on Oracle’s official careers site. Posted October 24, 2026. Check that it is still open and apply there.

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Job 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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