Description

Key Responsibilities

AI Strategy & Architecture

Define enterprise AI architecture, roadmaps, reference architectures, and governance standards.

Design secure, scalable, production-ready GenAI solutions across multiple LLM providers.

Lead architecture reviews and provide technical leadership for AI initiatives.

Identify AI opportunities across Finance, Operations, Risk, Underwriting, Claims, and Corporate functions.

LLM Evaluation & Optimization

Continuously evaluate emerging foundation models and AI platforms.

Benchmark models based on accuracy, reasoning, performance, security, enterprise readiness, and cost.

Develop model evaluation scorecards and recommendation frameworks.

Design advanced prompt engineering strategies to improve accuracy, consistency, and token efficiency.

Establish AI performance and ROI measurement frameworks.

Agentic AI & Automation

Architect AI agents and multi-agent solutions using tool calling, function calling, workflow orchestration, and MCP.

Design intelligent copilots, virtual assistants, and autonomous business workflows.

Enterprise AI Implementation

Lead GenAI solutions from ideation through production deployment.

Architect solutions using RAG, GraphRAG, hybrid search, vector databases, semantic search, and document intelligence.

Integrate AI capabilities with enterprise applications, data platforms, and knowledge systems.

Responsible AI & Governance

Establish AI security, privacy, governance, compliance, and responsible AI frameworks.

Implement guardrails, monitoring, risk controls, and human-in-the-loop processes.

Executive Advisory

Serve as a trusted AI advisor to senior business and technology leaders.

Translate complex AI capabilities into measurable business outcomes.

Lead AI workshops, executive briefings, use-case discovery, and business case development.

Support AI investment decisions and technology/vendor evaluations.

Required Qualifications

15+ years of overall technology experience.

7+ years of experience in AI/ML solutions and architecture.

3+ years of hands-on experience with Generative AI and LLM-based architectures.

Strong expertise in GenAI architecture, Agentic AI, multi-agent systems, AI copilots, LLMOps, and AI governance.

Experience with LLMs and foundation model ecosystems, including OpenAI, Anthropic, Google, Meta, Mistral, Cohere, or comparable platforms.

Strong experience with RAG, GraphRAG, vector databases, embeddings, hybrid search, and semantic search.

Hands-on experience with AI frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, or LlamaIndex.

Experience with cloud AI platforms such as Azure AI/Azure OpenAI, AWS Bedrock, Google Vertex AI, or Databricks AI.

Strong Python development skills and experience with REST APIs, microservices, and enterprise integration patterns.

Strong understanding of AI security, privacy, governance, and responsible AI practices.

Excellent executive communication, consulting, and stakeholder management skills.

Preferred Qualifications

Experience leading enterprise-wide AI transformation programs.

Experience working directly with Finance or other corporate business functions.

Experience designing AI cost-optimization and token-efficiency strategies.

Experience with emerging AI protocols, agent orchestration, and multi-agent architectures.

Experience evaluating and selecting AI vendors, models, and enterprise AI platforms.

Strong ability to mentor architects, engineers, and business teams.

Insurance or financial services industry experience is a plus

Key Skills

Education

Any Gradute