Distinguished AI Engineer

seeking a highly accomplished Distinguished AI Engineer to lead the architecture, engineering standards, and platform strategy for enterprise AI and Generative AI initiatives. This executive-level technical leadership role will define the future-state AI architecture, establish enterprise engineering standards, and guide the development of scalable, secure, observable, and cost-efficient AI platforms.

The ideal candidate has deep expertise in Large Language Models (LLMs), AI platform engineering, distributed systems, cloud infrastructure, MLOps/LLMOps, and enterprise architecture, with a proven track record of delivering AI platforms at enterprise scale., * Define the target-state architecture for enterprise AI platforms, LLM platforms, model hubs, AI gateways, Retrieval-Augmented Generation (RAG) services, agentic AI frameworks, orchestration layers, and model-serving infrastructure.

• Establish enterprise engineering standards for AI Software Development Lifecycle (AI SDLC), LLMOps, MLOps, model evaluation, release management, operational resilience, production support, and platform governance.
• Design secure, scalable, highly available, and cost-optimized AI inference platforms across cloud, hybrid, private cloud, and containerized environments.
• Develop enterprise guardrail frameworks addressing hallucination mitigation, bias monitoring, harmful content controls, prompt injection defense, data leakage prevention, explainability, and human oversight.
• Lead architecture reviews and provide technical assurance for high-impact AI initiatives across enterprise architecture, technology, and risk governance forums.
• Collaborate with Cybersecurity, Risk Management, Compliance, Legal, Audit, Product Management, Engineering, and Business leaders to ensure AI solutions align with enterprise governance and regulatory requirements.
• Mentor Principal Engineers and senior technical leaders while establishing reusable reference architectures, engineering playbooks, implementation patterns, and best practices.
• Evaluate emerging AI technologies, platforms, frameworks, and infrastructure to recommend enterprise adoption based on business value, maturity, scalability, cost, and regulatory considerations.
• Drive innovation across enterprise AI strategy while ensuring operational excellence and engineering consistency.

• 10+ years of experience in Artificial Intelligence, Machine Learning, Distributed Systems, Enterprise Architecture, Platform Engineering, or related disciplines.
• Deep expertise with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings, model serving, AI orchestration, AI evaluation frameworks, and enterprise AI infrastructure.
• Proven experience defining enterprise architecture, technical standards, and engineering governance across multiple development teams.
• Strong understanding of distributed training, GPU infrastructure, inference optimization, observability, model governance, resiliency, and cloud-native AI platforms.
• Extensive experience with Kubernetes, containers, cloud platforms, APIs, microservices, and distributed computing architectures.
• Strong leadership, mentoring, stakeholder management, and executive communication skills.
• Ability to influence enterprise architecture, engineering, risk, compliance, and business leadership across large-scale transformation initiatives., * Experience within Banking, Financial Services, FinTech, or other highly regulated enterprise environments.
• Experience designing enterprise AI platforms, private LLM deployments, internal model hubs, AI gateways, multi-cloud AI architectures, or enterprise AI operating models.
• Familiarity with Responsible AI, AI Governance, Model Risk Management, Technology Risk Controls, Audit Requirements, and Enterprise Compliance frameworks.
• Experience leading enterprise AI transformation initiatives across global organizations.