Director, Global Forward Deployed AI Programs

Johnson & Johnson•Raritan, NJ

7d•Onsite

About The Position

The Director, Global AI Forward Deployed Programs is part of Johnson & Johnson’s AI Strategy and Execution team in the Global Commercial Strategy Organization (GCSO). The leader embeds with global Marketing, Medical Affairs, and Market Access teams to build and ship production Generative AI and Agentic AI solutions addressing business needs. This global role establishes technical and operational standards for AI pilots and scaled solutions across GCSO and influences regional AI teams, with an emphasis on action and measurable impact. The Director sets success metrics for AI products from development through delivery and coordinates product development and delivery across regions. The role remains close to technical work, reviewing architectures, debugging production issues, and working alongside data scientists, data engineers, advanced analytics professionals, and vendor partners. It also builds the Forward Deployed Engineering capability, develops engineering talent, and promotes AI adoption across GCSO. The role defines standards for agent harnesses, evaluation, and production deployment in a regulated commercial environment. It owns the path from prototype to production, including continuous evaluation, CI/CD, staged rollouts, versioning, rollback plans, observability, and incident response. The Director ensures solutions meet regulatory, privacy, ethical, and medical/legal/regulatory standards, and creates reusable playbooks, harness components, evaluation frameworks, and deployment templates. The position is based in Raritan, NJ or Horsham, PA, requires travel between both locations, and may require travel to business partner and global sites up to 25%.

Requirements

Bachelor’s degree in Computer Science, Engineering, Operations Research, or a related field, or equivalent experience.
At least 7 years of experience in software engineering, ML/AI engineering, solutions architecture, or a technical client-facing role such as forward deployed engineering or technical consulting.
At least 5 years of people management experience leading engineers in a delivery, services, or embedded/Forward Deployed Engineering-style organization.
Track record of hiring, developing, and retaining strong technical talent.
Experience building a Forward Deployed Engineering capability from scratch.
Hands-on experience shipping production LLM applications and AI agents, including RAG architectures, tool use, multi-step orchestration, and prompt engineering.
Experience designing and running LLM evaluations, including evaluation datasets, quality metrics, automated and human-in-the-loop review, and using results to make release decisions.
Experience deploying and operating production AI systems, including CI/CD, monitoring and observability, cost and latency management, and enterprise security, privacy, and compliance requirements.
Experience working directly with business stakeholders on technical implementations and navigating complex organizational dynamics in a large enterprise.
Executive presence and ability to engage in strategic discussions with senior leaders as well as hands-on debugging with engineers.
Strong written and verbal communication skills, including ability to explain technical complexity to diverse audiences.
Ability to thrive in ambiguity and enthusiasm for building something new.
Ability to work from Raritan, NJ or Horsham, PA and travel between both locations; additional travel to business partner and global sites may be required up to 25%.

Nice To Haves

Master’s or PhD in a related field.
Pharma, healthcare, or regulated industry experience.
Familiarity with Salesforce, omnichannel marketing ecosystems, and field engagement workflows.

Responsibilities

Build the Forward Deployed Engineering competency and influence teams across GCSO and regional organizations.
Partner with regions, R&D, and Supply Chain to develop and retain engineering talent with technical depth and business instincts.
Set technical standards and OKRs tied to business outcomes and AI adoption goals.
Establish operating cadences, including standups, retrospectives, and engagement reviews.
Partner with the AI fluency leader on technical skill building, especially in agentic AI.
Define AI use cases, scope engagements, and align success criteria before work begins.
Define and monitor financial impact metrics, including token costs and AI product ROI.
Review architectures, harness designs, evaluation results, and code produced by the team and vendor partners.
Ensure solutions are high-quality, reliably evaluated, production-ready, and integrated into the AI ecosystem, including Engagement.ai and Connext.
Lead technical discovery, prototype solutions, and debug complex issues alongside the team and vendor partners.
Ensure solutions meet regulatory, privacy, ethical, and MLR standards, partnering with Technology, Privacy, and Compliance from design through deployment.
Create reusable playbooks, starter repositories, integration templates, and an internal knowledge base.
Partner with Technology, Data Science, and Product teams to turn field insights into platform and product improvements.
Represent business needs in AI planning and roadmap discussions.
Support evaluation of external AI vendors, model providers, and enterprise platforms, and contribute hands-on deployment experience to build-versus-buy decisions.
Champion AI adoption across GCSO and help business teams move from pilots to sustained use.
Define standards for agent harnesses, including orchestration, tool and API integrations, context and memory management, guardrails, and human-in-the-loop checkpoints.
Establish evaluation practices, including task-specific evaluation sets, automated regression suites, LLM-as-judge and human review workflows, and release quality thresholds.
Ensure evaluations run continuously to test model upgrades, prompt changes, and new data sources against agreed benchmarks.
Own the path from prototype to production with Technology and platform teams, including CI/CD, staged rollouts, prompt and model versioning, and rollback plans.
Implement observability for deployed solutions, including tracing, cost and latency monitoring, quality and drift tracking, and incident response.
Feed production issues back into evaluations and harness improvements, and incorporate reusable components into team playbooks.

Benefits

Medical, dental, and vision insurance.
Life insurance and short- and long-term disability insurance.
Business accident insurance and group legal insurance.
Consolidated retirement plan (pension) and 401(k) savings plan.
Eligibility to participate in the long-term incentive program.
Vacation: 120 hours per calendar year.
Sick time: 40 hours per calendar year; 56 hours for employees residing in Washington State.
Holiday pay, including floating holidays: 13 days per calendar year.
Work, Personal and Family Time: up to 40 hours per calendar year.
Parental leave: 480 hours within one year of a child’s birth, adoption, or foster care placement.
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.