Senior AI Integration Engineer

We have been engaged in a national search for a Senior AI Integration Engineer to help lead the organization's enterprise AI strategy and adoption. You will play a pivotal role in evaluating AI technologies, defining enterprise standards, guiding vendor selection, and integrating AI solutions across the organization.

This role combines hands‑on engineering with technical leadership, partnering with business leaders, Data Science, Cloud Engineering, Dev Ops, Cybersecurity, and Enterprise Architecture to build secure, scalable, and governed AI solutions. You will establish best practices for AI integration, oversee AI agent development, and help shape the future of AI across the enterprise.

In this role, the Senior AI Integration Engineer will:

• Design, develop, and implement secure, scalable integrations between AI platforms (LLMs, machine learning models, intelligent agents) and enterprise applications using APIs and cloud‑native technologies.
• Partner with technology leadership to define and execute the organization's enterprise AI platform strategy and long‑term AI adoption roadmap.
• Lead technical evaluations of AI platforms and vendors, participate in RFI/RFP processes, perform proof‑of‑concept assessments, and recommend enterprise AI solutions.
• Build, optimize, and deploy AI‑enabled solutions using modern AI frameworks, including Azure OpenAI and other enterprise AI technologies.
• Design and implement prompt engineering strategies, Retrieval‑Augmented Generation (RAG), LLM optimization, and NLP solutions.
• Build and maintain MLOps pipelines for model deployment, monitoring, observability, and lifecycle management.
• Establish AI governance standards, technical guardrails, reusable integration patterns, and best practices to ensure secure, ethical, and compliant AI implementations.
• Provide technical oversight and architectural guidance for AI agents and AI‑enabled applications developed internally and by third‑party vendors.
• Integrate structured and unstructured enterprise data sources to support AI initiatives and improve business processes.
• Monitor AI performance through model observability, prompt optimization, hallucination detection, latency monitoring, cost tracking, and automated testing.
• Collaborate with business and technology stakeholders to identify, prioritize, and implement AI use cases.
• Serve as a technical mentor and trusted advisor, communicating complex AI concepts to both technical and non‑technical audiences while helping establish enterprise AI standards.

The appropriate individual will have clearly demonstrated experience in the following:

• Bachelor's degree in Computer Science, Artificial Intelligence, Engineering, or a related technical discipline (or equivalent experience).
• 7 - 10+ years of experience designing and implementing AI and Machine Learning solutions within enterprise environments.
• Strong programming experience with Python, Java, or similar object‑oriented languages.
• Hands‑on experience with enterprise AI platforms such as Azure OpenAI and modern AI frameworks.
• Deep expertise in API development, cloud platforms, distributed systems, microservices, and enterprise integrations.
• Experience with Large Language Models (LLMs), prompt engineering, vector databases, Retrieval‑Augmented Generation (RAG), AI agents, and Natural Language Processing (NLP).
• Designing and supporting MLOps pipelines and CI/CD deployment practices.
• Knowledge of AI observability, prompt/model monitoring, hallucination detection, guardrails, and model performance optimization.
• Establishing AI governance, security, privacy, and responsible AI practices.
• Strong strategic thinking, problem‑solving, communication, and leadership skills with the ability to influence cross‑functional teams and drive enterprise AI…