Director, Global Forward Deployed AI Programs

Description

The company is a healthcare business working across Innovative Medicine and MedTech, and the role sits in its Global Commercial Strategy Organization (GCSO), in the AI Strategy and Execution team.

This is a global leadership role that builds productized AI solutions for GCSO and guides regional AI teams. You will embed with Marketing, Medical Affairs, and Market Access at the global level to build and ship production Generative AI and Agentic AI solutions for internal customers.

You will set the technical and operational standard for every pilot and scaled AI solution across the commercial organization, while staying close enough to the work to review architectures, debug production issues, and pair with data scientists, data engineers, and analytics professionals. Your main impact comes from the global standards you set and the products you build. You will define success metrics from development through delivery and coordinate regions on AI product delivery.

Job category: Professional. Function: Data Analytics and Computational Sciences. Sub-function: Data Science Portfolio Management.

Responsibilities

• Build the forward deployed engineering capability across GCSO and the regions, influencing without direct authority. Work with regions, R&D, and Supply Chain to grow and keep engineers with strong technical depth and business judgment.
• Set technical standards and OKRs linked to business outcomes and AI adoption. Run regular cadences such as standups, retrospectives, and engagement reviews to keep the team aligned.
• Work with the AI fluency leader to build technical skills, especially in agentic AI, across GCSO.
• Define AI use cases, scope the work, and agree success criteria before each engagement starts.
• Define and track financial impact metrics, including token costs and AI product ROI.
• Review architectures, harness designs, eval results, and code from the team and vendor partners. Make sure solutions are high quality, reliable, production ready, and integrated with the AI ecosystem, such as Engagement.ai and Connext.
• Stay hands-on: lead technical discovery, prototype solutions, and debug complex issues with the team and vendors.
• Make sure every solution meets regulatory, privacy, ethical, and medical, legal, and regulatory (MLR) standards, working with Technology, Privacy, and Compliance from design to deployment.
• Build playbooks, starter repositories, integration templates, and an internal knowledge base from field experience.
• Work with J&J Technology, Data Science, and Product teams to turn field insights into platform and product improvements. Represent the business in AI planning and roadmap discussions.
• Support evaluation of external AI vendors, model providers, and enterprise platforms, bringing deployment experience to build-versus-buy decisions.
• Drive AI adoption across GCSO and help business teams move from pilots to sustained use.
• Set team standards for agent harnesses, covering orchestration, tool and API integration, context and memory, guardrails, and human-in-the-loop checkpoints for a regulated commercial setting.
• Create an evaluation process for every engagement: task-specific eval sets built with business and MLR partners, automated regression suites, LLM-as-judge and human review, and quality thresholds that must be met before release.
• Run evals continuously, not only at launch, so model upgrades, prompt changes, and new data sources are tested against agreed benchmarks before reaching users.
• Own the path from prototype to production with Technology and platform teams, including CI/CD for AI applications, staged rollouts, prompt and model versioning, and rollback plans.
• Set up observability for deployed solutions: tracing, cost and latency monitoring, quality and drift tracking, and incident response. Feed production issues back into evals and harness improvements.
• Add reusable harness components, eval frameworks, and deployment templates to the playbooks so each engagement starts further ahead.

Requirements

• Bachelor's degree in Computer Science, Engineering, Operations Research, or a related field, or equivalent experience.
• A Master's or PhD in a related field is preferred.
• 7+ years in software engineering, ML or AI engineering, solutions architecture, or a technical client-facing role such as forward deployed engineering or technical consulting.
• 5+ years managing engineers in a delivery, services, or embedded or Forward Deployed Engineering-style organization, including hiring, developing, and retaining strong technical talent.
• Experience building an FDE capability from scratch.
• Hands-on experience shipping production LLM applications and AI agents, including RAG, tool use, multi-step orchestration, and prompt engineering.
• Proven experience designing and running LLM evaluations: building eval datasets, defining quality metrics, running automated and human-in-the-loop review, and using results for release decisions.
• Experience deploying and operating AI systems in production, including CI/CD, monitoring and observability, cost and latency management, and meeting enterprise security, privacy, and compliance requirements.
• Experience working directly with business stakeholders on technical implementations and handling complex organizational dynamics in a large enterprise.
• Executive presence, able to move between strategy discussions with senior leaders and hands-on debugging with engineers.
• Strong written and verbal communication, translating technical complexity into clear stories for different audiences.
• Comfortable with ambiguity and motivated by building something new.
• Pharma, healthcare, or regulated industry experience is preferred.
• Familiarity with Salesforce, omnichannel marketing ecosystems, and field engagement workflows is a plus.
• Required skills: Advanced Analytics, Business Case Modeling, Consulting, Data Privacy Standards, Data Science, Data Structures, Digital Fluency, Digital Strategy, End to End Implementation, Global Market, Master Data Management (MDM), Negotiation, Product Portfolio Management, Quality Control (QC), Resource Planning, Tactical Planning, Technical Credibility.

Conditions

Based in Raritan, NJ or Horsham, PA, with required travel between both sites. Additional travel to business partner and global sites as needed, up to 25%.

Location: Raritan, New Jersey, United States of America.

The anticipated base pay range is $164,000 to $282,900 USD.

The company is committed to an inclusive interview process. Candidates needing an accommodation should use the contact route listed on the careers site.

Benefits

• Medical, dental, vision, life insurance, short- and long-term disability, business accident insurance, and group legal insurance, subject to plan terms.
• Consolidated retirement (pension) plan and savings plan (401(k)), subject to plan terms.
• Eligibility for the long-term incentive program.
• Vacation: 120 hours per calendar year. Sick time: 40 hours per calendar year, or 56 hours for employees in Washington State.
• 13 days of holiday pay per calendar year, including floating holidays.
• Up to 40 hours per calendar year of work, personal, and family time.
• Parental leave: 480 hours within one year of the birth, adoption, or foster care of a child.
• Condolence leave: 30 days for an immediate family member and 5 days for an extended family member.
• Caregiver leave: 10 days. Volunteer leave: 4 days. Military spouse time off: 80 hours.
• Eligibility depends on plan terms and date of hire. Full benefit details are available on the company's benefits page.