# IntePros — Director, AI Engineering

- Generated: 2026-08-27 10:00:03 AM EDT
- Original JD: https://www.linkedin.com/jobs/view/4459001281/
- Provider: LinkedIn
- Location: United States
- Work model: Remote; travel to Philadelphia once a month or quarter
- Posting age: 1 day ago
- Applicants: 55 applicants
- Compensation: $150,000.00/yr - $175,000.00/yr
- Travel: Philadelphia office once monthly or quarterly; duration is not disclosed
- Positioning track: Technical manager
- Fit outcome: FAIL — Keith explicitly overrode the compensation failure and requested generation
- Fit score before hard-gap override: 100.0%

## Central mandate

Architect, implement, operationalize, govern, and continuously improve enterprise GenAI and agentic solutions in a regulated medical-device/packaging environment.

## Evidence map

- **Senior technical authority for enterprise AI architecture:** Direct: AI founder, VP AI/ML, AWS AI/ML specialist, and enterprise architecture leadership.
- **10+ years in software/platform/AI/data engineering:** Direct: decades of software, cloud, data, and AI engineering through production.
- **5+ years leading technical teams and functions:** Direct: led teams of 7, 11, 24, 25, and global communities of 80+ specialists.
- **GenAI, LLMs, RAG, agents, and modern AI architectures:** Direct: production AssistX architecture across 70+ automations and 20+ workflows.
- **Cloud-native APIs, integration, security, and supportability:** Direct: AWS, SaaS, API, distributed-system, integration, and operations delivery.
- **MLOps, LLMOps, monitoring, observability, and lifecycle:** Direct: production AI operations plus MassMutual governance and SageMaker lifecycle controls.
- **Cybersecurity, privacy, compliance, and Responsible AI:** Direct: privacy-rights platform, AI governance, HIPAA, FDA, and auditability evidence.
- **Vendors, contractors, offshore teams, and partners:** Direct: distributed/offshore teams and vendor-supported enterprise delivery.
- **Regulated life-science, healthcare, or manufacturing context:** Direct: Ph.D., pharma/bioinformatics, FDA-cleared medical technology, and regulated platforms.
- **Emerging AI platforms and stakeholder translation:** Direct: evaluated multiple model/platform families and advised 200+ enterprises.

## Hard and material gaps

- Hard gap: the disclosed $150,000-$175,000 base range tops out below Keith's $200,000 threshold.
- Material caveat: monthly Philadelphia travel could approach Keith's 5% ceiling depending on trip duration; quarterly travel would be comfortably within it.
- Azure-specific tooling is not source-supported, although the posting also accepts AWS AI Services, Bedrock, Claude, Gemini, or similar platforms.

## Artifact metadata

- Resume: https://bit.ly/4c8ic5C
- Cover letter: https://bit.ly/4gRvRk5
- Resume pages: 2
- Cover-letter pages: 1
- Keyword overlap: 20/20 (100.0%)
- Missing significant keywords: none
- Google Drive used: no

## Full normalized job description

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 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 GCP 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.