What are the responsibilities and job description for the Artificial Intelligence (AI) Specialist position at Paul Murphy Associates?
Title: Artificial Intelligence (AI) Specialist
Location: Chicago or New York (Hybrid 3 days in office)
Our client is seeking an AI Specialist to own and execute their enterprise-wide AI strategy and tactics. In this role, you will bridge the gap between cutting-edge AI capabilities and institutional-grade security in a financial services setting. Their organization is explicitly pro-AI: adopting AI and embedding it into daily workflows is a formal corporate KPI across every department - from software engineering and product management to accounting, legal, and HR.
You will serve as the core catalyst enabling staff to safely maximize their output while ensuring zero enterprise data leaks into external training sets.
Responsibilities
1. Strategic Governance & Security Controls
- AI Strategy & Roadmap: Formulate and maintain the company’s AI adoption roadmap, continuously evaluating the performance, cost, and security trade-offs of frontier models (e.g., Anthropic Claude, Google Gemini, OpenAI) and specialized financial LLMs.
- Strict Data Isolation: Enforce zero-data-retention and data isolation protocols across all AI integrations, guaranteeing that company data is never used for external model training.
- Access Control & Auditing: Work with security engineering to implement centralized identity and access management (IAM), credential management, role-based access control (RBAC), and full audit logging for model endpoints.
2. Architecture & Infrastructure
- Managed Cloud Solutions: Architect, deploy, and maintain secure enterprise AI integrations leveraging cloud-based platforms such as, for example, AWS Bedrock, GCP Vertex AI, or Azure OpenAI.
- MCP & Agent Frameworks: Evaluate, standardise, and deploy protocol architectures like Model Context Protocol (MCP) to securely connect frontier models with internal databases, tools, and enterprise applications.
- Heuristics & Optimization: Establish cost/performance heuristics (model routing, prompt caching, token budgets) and embed them into user interfaces so staff naturally leverage the most effective model for each task.
3. Enterprise-Wide Upskilling & Enablement
- Cross-Functional Enablement: Serve as the hands-on AI advisor for all teams—coaching developers using AI for code generation/testing, accounting teams automating month-end closeouts, legal teams conducting contract reviews, and marketing staff generating copy and presentations.
- Custom Agents & Tooling: Assist staff across all functional units in building, deploying, and maintaining custom GPTs/agents, workflows, and prompts tailored to specific domain tasks.
- Training Programs: Design and execute structured training curricula, bootcamps, and office hours to elevate AI literacy and practical competency across the entire headcount.
Requirements
- Production & Corporate AI Track Record: Demonstrated experience successfully implementing, operationalizing, and driving adoption of AI tools and LLM-powered workflows within a professional, team-based environment—moving beyond personal usage to deliver measurable productivity gains, custom agentic systems, or automated workflows at scale across cross-functional teams.