AI Solution Architect

Job Description

As an AI Solution Architect at Oracle, you will be instrumental in defining AI/ML architectures, spearheading marquee customer engagements, and championing cutting-edge solutions in Generative AI (GenAI), Large Language Models (LLMs), AI Agents, and Responsible AI frameworks. This pivotal role requires 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 diverse 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 is 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 Go-To-Market initiatives (proposals, bid defense, executive workshops).

Qualifications & Experience

• 16–20 years in technology, with 8+ years specifically 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.

Key skills/competency

• Enterprise AI Architecture
• Generative AI & LLMs
• AI Agent Orchestration
• Oracle Cloud Infrastructure (OCI)
• MLOps & Governance
• Responsible AI Frameworks
• Executive Communication
• RAG Architectures
• Vector Databases
• Prompt Engineering