IntePros is currently looking for a
Director, AI Engineering to join one of our growing medical device/packaging clients in Philadelphia, PA. This position will be remote with travel travel to the Philadelphia office once a month/quarter. The
Director, AI Engineering is responsible for architecting, implementing, operationalizing, and continuously improving AI solutions that drive innovation, operational efficiency, customer experience, and business value across the enterprise. Partnering closely with business stakeholders, technology teams, cybersecurity, quality, infrastructure, and external partners, this position evaluates AI opportunities and translates strategic priorities into scalable, secure, compliant, and supportable solutions. The Director, AI Engineering provides technical leadership across AI architecture, large language models (LLMs), retrieval augmented generation (RAG), agentic workflows, AI operations, and emerging technologies while establishing engineering standards, technical controls, and best practices that enable responsible AI adoption
throughout client and support execution of the enterprise AI roadmap.
Director, AI Engineering responsibilities:
- Serve as client's senior technical leader for AI engineering, providing architectural direction, technical oversight, and implementation guidance for enterprise AI initiatives.
- Partner with business and technology stakeholders to evaluate AI opportunities and determine appropriate technical approaches, architectures, and implementation strategies.
- Define and maintain AI engineering standards, reference architectures, design patterns, and best practices that support scalable, secure, and supportable solutions.
- Lead the architecture, design, implementation, and operationalization of AI solutions across customerfacing and internal business use cases.
- Establish solution patterns for generative AI, retrieval augmented generation (RAG), agentic workflows, intelligent assistants, and AI-enabled automation.
- Design and oversee AI integrations across enterprise platforms, business applications, digital products, and the Enterprise Data Platform.
- Drive technical decision-making throughout the AI solution lifecycle from ideation through production deployment and ongoing optimization.
- Establish and maintain AI engineering, operational, MLOps, and LLMOps practices across development, testing, validation, and production environments.
- Implement processes for model lifecycle management, monitoring, observability, testing, version control, and continuous improvement.
- Ensure AI solutions are engineered for scalability, reliability, maintainability, supportability, and operational readiness.
- Partner with Cybersecurity, Infrastructure, Quality, and Data Engineering teams to implement technical controls supporting client's AI governance framework.
- Partner with Legal, Procurement, Cybersecurity, Quality, and business stakeholders to assess the technical feasibility, operational impact, and implementation requirements of AI-related contractual commitments, security controls, data protection requirements, and regulatory obligations.
- Support AI risk assessments, validation activities, audit readiness efforts, and governance reviews as required.
- Ensure AI solutions align with regulatory requirements, security standards, privacy requirements, responsible AI principles, and applicable quality processes.
- Monitor, forecast, and optimize AI-related platform, licensing, model consumption, infrastructure, and operational costs.
- Establish metrics and reporting related to AI adoption, operational effectiveness, solution performance, cost optimization, and business value realization.
- Serve as the primary technical lead for AI-related vendors, consultants, contractors, and implementation partners.
- Direct and oversee AI solution delivery performed by external development teams and strategic technology partners.
- Evaluate emerging AI technologies, products, platforms, models, service providers, and industry practices to support technical decision-making and innovation.
- Ensure partner-delivered solutions align with client architecture standards, quality expectations, delivery commitments, and business objectives.
- Build and mature client's AI engineering capability, including future team development, mentoring, knowledge sharing, and engineering excellence.
- Foster a culture of innovation, responsible experimentation, continuous improvement, and technical learning across the AI engineering function.
- Completes all job duties in compliance with company policies, SOPs, safety rules, and all applicable federal, state, local, quality, and regulatory requirements, including OSHA, FDA, and cGMP standards.
- This position may require overtime and/or weekend work.
- Knowledge of and adherence to all client, cGMP, and Google Cloud Platform policies, procedures, rules.
- Attendance of work is an essential function of this position.
- Performs other duties as assigned by Manager/Supervisor
Director, AI Engineering Qualifications: Required: - Bachelor's degree in Computer Science, Engineering, Information Technology, Data Science, Artificial Intelligence, or a related technical field.
- 10+ years of progressive experience in software engineering, platform engineering, AI engineering, data engineering, or related technology disciplines, including experience leading complex enterprise technology initiatives.
- 5+ years of leadership experience managing technical teams, projects, vendor-delivered solutions, or engineering functions.
- Demonstrated experience serving as a senior technical authority for AI initiatives, including evaluation of AI use cases, selection of technical approaches, architectural decision-making, technical governance, vendor oversight, and operationalization of AI solutions.
- Experience with Generative AI, Large Language Models (LLMs), Retrieval Augmented Generation (RAG), agentic AI systems, enterprise AI platforms, and modern AI solution architectures.
- Strong understanding of cloud-native architectures, APIs, integration patterns, and the design of scalable, secure, and supportable enterprise solutions.
- Experience establishing and supporting operational practices for AI solutions, including lifecycle management, monitoring, governance, observability, and continuous improvement.
- Strong understanding of cybersecurity, privacy, compliance, responsible AI principles, and implementation of technical controls within regulated or governance-driven environments.
- Experience working with external vendors, consulting partners, contractors, managed service providers, and offshore delivery teams to deliver technology solutions and business outcomes.
- Demonstrated ability to evaluate emerging technologies, communicate effectively with technical and business stakeholders, and translate strategic opportunities into scalable technical solutions.
Preferred: - Master's degree in computer science, Artificial Intelligence, Data Science, Engineering, or a related field.
- Experience with Microsoft Azure AI Services, Azure OpenAI, Microsoft Copilot, AWS AI Services, Amazon Bedrock, Anthropic Claude, Google Gemini, or similar enterprise AI platforms.
- Experience establishing MLOps, LLMOps, AI observability, model monitoring, and AI governance capabilities within enterprise environments.
- Experience designing and deploying AI-enabled digital products, enterprise knowledge management solutions, intelligent automation, agentic workflows, and AI-driven business process transformation initiatives.
- Pharmaceutical, life sciences, healthcare, manufacturing, or other highly regulated industry experience, including support for validation, audit readiness, quality systems, or regulatory compliance requirements.
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