Senior AI Engineer

Madison-Davis; New York (NY); On-site; USD 140,000 - 200,000; Full time

Job summary

Madison-Davis, LLC is seeking a hands-on Senior AI Engineer to advance secure enterprise adoption of Generative AI across infrastructure, apps, and data. The role focuses on security guardrails, governance controls, and secure integration architecture.

You will apply LLM, AI agent, MCP, Python, and enterprise API expertise to protect information, constrain unauthorized activity, and enable responsible AI deployment.

Qualifications

• 5-8 years of software, cloud, or AI engineering experience.
• 2+ years of enterprise GenAI/LLM experience.
• Strong Python development and enterprise integration capabilities.
• Knowledge of AI security risks, governance, and access controls.

Responsibilities

• Evaluate security risks across enterprise AI applications, agents, and integrations.
• Design and implement practical security guardrails for LLM applications and AI workflows.
• Architect secure AI connections to enterprise APIs, infrastructure, and internal systems.
• Develop controls for authentication, authorization, data access, and agent behavior.
• Translate governance requirements into reusable technical standards and enforceable controls.
• Collaborate with infrastructure, cybersecurity, and engineering teams on secure AI deployment.
• Implement testing, logging, monitoring, and evaluation for AI security controls.
• Use Python and modern engineering practices to operationalize secure AI solutions.

Skills

Strong architecture judgment

Technical collaboration

Education

Bachelor's degree or equivalent

Tools

Python

MCP or comparable integration technologies

Enterprise APIs

Job description

A leading professional services organization is seeking a hands‑on Senior AI Engineer to support secure enterprise adoption of Generative AI across infrastructure, applications, internal systems, and business data. The position focuses on technical security guardrails, secure integration architecture, and the engineering implementation of AI governance controls. The ideal candidate understands LLMs, AI agents, MCP, Python, and enterprise APIs and can apply that expertise to protect sensitive information, restrict unauthorized activity, and enable responsible AI adoption.

RESPONSIBILITIES

• Evaluate security risks across enterprise AI applications, agents, and integrations.
• Design and implement practical security guardrails for LLM applications and AI workflows.
• Architect secure AI connections to enterprise APIs, infrastructure, and internal systems.
• Develop controls for authentication, authorization, data access, and agent behavior.
• Translate governance requirements into reusable technical standards and enforceable controls.
• Collaborate with infrastructure, cybersecurity, and engineering teams on secure AI deployment.
• Implement testing, logging, monitoring, and evaluation for AI security controls.
• Use Python and modern engineering practices to operationalize secure AI solutions.

Role Requirements

• 5-8 years of software, cloud, or AI engineering experience.
• 2+ years of enterprise GenAI/LLM experience.
• Strong Python development and enterprise integration capabilities.
• Practical understanding of agents, LLM applications, tool calling, and orchestration.
• Familiarity with MCP or comparable integration technologies.
• Knowledge of AI security risks, privacy, and access controls.
• Ability to implement technical security controls and operationalize governance.
• Strong architecture judgment and technical collaboration skills.
• Relevant bachelor's degree or equivalent practical experience.

PREFERRED EXPERIENCE

• AI security guardrail or governance framework implementation.
• Secure agentic workflows or MCP server development.
• RAG, semantic search, and enterprise data retrieval.
• Claude Code, Anthropic APIs, or Azure AI services.
• Experience in information-sensitive enterprise environments.