Oracle
Consulting Technical Manager
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.
Job Title: Principal AI Architect - Consulting Technical Manager
Location: India (Global role with cross-regional collaboration; requires flexible time-zone support)
Experience: 15–20 years total, with at least 8+ years in AI/ML solutioning and enterprise architecture
Job Type: Full-time, Individual Contributor (Enterprise Architect calibre)
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.
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