Job Description

You will define AI/ML architectures, lead marquee customer engagements, and evangelize cutting-edge solutions in Generative AI (GenAI), Large Language Models (LLMs), AI Agents, and Responsible AI frameworks. The role demands a unique balance of strategic vision, hands-on technical delivery, and market-facing thought leadership.


Core Competencies


Enterprise Architecture - Defining AI-enabled enterprise architectures that scale across industries. Generative AI & Agents - Proven expertise in LLMs, multi-modal AI, AI agent orchestration, and prompt/flow engineering. Cloud & Multi-cloud Strategy - Expert in Oracle Cloud Infrastructure (OCI); experience with AWS, Azure, GCP highly valued. AI/ML Engineering & MLOps - Strong grounding in ML frameworks (LangChain, HuggingFace, PyTorch, TensorFlow), CI/CD, observability, and governance. AI Security & Responsible AI - Knowledge of data privacy, fairness, explainability, model risk & compliance frameworks. Executive Engagement - Ability to communicate AI vision and ROI at board/executive level, while guiding technical teams on design/delivery. Innovation & GTM - Strong orientation towards IP reuse, accelerators, and GTM initiatives (proposals, bid defense, executive workshops).
Qualifications & Experience


16-20 years in technology, with 8+ years in AI/ML, Data Science, or Advanced Analytics. Demonstrated track record in enterprise-scale AI/ML adoption--from discovery to production rollout. Proven hands-on expertise in GenAI, LLM fine-tuning, multi-modal AI, and intelligent agents. Deep experience with cloud-native deployments, vector databases, RAG architectures, and hybrid data pipelines. Strong expertise in MLOps, governance, and lifecycle management of AI models. Experience in executive-facing roles (CxO briefings, board-level AI strategy sessions). Bachelor's/Master's in Computer Science, Data Science, AI, or equivalent. PhD preferred but not mandatory.
Contributions to AI thought leadership: patents, whitepapers, conference talks, or AI community initiatives.



Key Responsibilities


Enterprise AI Leadership

Drive enterprise-wide AI/ML architecture strategy, ensuring alignment with business outcomes, data strategy, security, and compliance.
Solution Design & Delivery

Architect, prototype, and deliver production-grade AI systems across GenAI, LLMs, multi-modal AI, RAG pipelines, and intelligent agents.
CxO Engagement

Act as a trusted advisor to CIOs/CTOs/CDOs on AI adoption strategy, cloud-native transformation, and scaling AI beyond PoCs into production.
Hands-on Technical Authority

Remain deeply hands-on in architecting and integrating AI into enterprise landscapes (Fusion, EBS, custom apps, cloud-native stacks).
Governance & Standards

Establish AI architecture blueprints, reusable patterns, and governance frameworks (LLMOps, model risk management, AI security, EU AI Act compliance).
Thought Leadership

Represent the practice in customer-facing demos, conferences, and whitepapers; influence Oracle's AI GTM and innovation roadmap.
Cross-Studio Collaboration

Partner with Cloud, Data & Analytics, and Security Studios to deliver end-to-end enterprise transformation solutions.
Market & Innovation Focus

Track global AI trends, vendor ecosystems (OpenAI, Cohere, Anthropic, HuggingFace), and continuously infuse market-leading innovation into delivery.