Associate Director, Safety Data Solutions Architect

Johnson & Johnson is hiring an Associate Director, Safety Data Solutions Architect. It pays $137k-$236k a year and Level rates it ; you can apply on Johnson & Johnson.

Level's read on this job

Level rates this solutions architect role Works on AI ●●●○: the daily work is on AI products, without building the model.
The posting mentions Vertex AI, prompt engineering and RAG among its tools and skills.
Level classes it as an executive role.
Johnson & Johnson has 1,800+ other open roles on Level.
Posted in the last few days.

AI in this role

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At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

Job Function:

Data Analytics & Computational Sciences

Job Sub Function:

Data Science

Job Category:

Scientific/Technology

All Job Posting Locations:

Horsham, Pennsylvania, United States of America, Titusville, New Jersey, United States of America

Job Description:

About Innovative Medicine

Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.

Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.

Learn more at https://www.jnj.com/innovative-medicine

Role Overview

Johnson & Johnson Global Medical Safety (GMS) is seeking an Associate Director, Safety Data Solutions Architect to lead the target architecture, standards, and delivery roadmap for safety analytics on Google Cloud Platform (GCP). This role provides solution architecture leadership for pharmacovigilance and safety analytics, translating safety science needs into validated, scalable, and compliant data and AI capabilities. Partner with Safety Analytics (SA) Data Scientists on LLM/GenAI use cases to ensure platform guardrails, retrieval/inference patterns, and compliance controls. The Architect will coordinate Principal-level data engineers and cross-functional teams to deliver trusted, inspection-ready data products for downstream analytics and AI services. The role emphasizes architecture strategy, regulatory readiness, and responsible AI, while ensuring alignment to enterprise patterns, cost efficiency, and operating excellence. A selective hands-on component focuses on reference implementations and “golden-path” templates that accelerate team adoption.

Key Responsibilities

Translate architecture strategy into measurable outcomes by establishing baselines, performance indicators, and benefit-realization measures for data onboarding speed, solution reuse, platform reliability, inspection readiness, cost efficiency, and time to insight for safety scientists.
Partner with Safety, Product, Data Science, and Technology leaders to translate business capabilities and scientific workflows into a multi-year data and platform roadmap, including build-versus-buy recommendations, investment sequencing, adoption and value measures, and the rationalization and retirement of legacy technologies.
Establish governed AI lifecycle patterns and platform controls for the evaluation, approval, versioning, deployment, monitoring, and reproducibility of AI-enabled solutions, including defined human oversight, provider portability, rollback mechanisms, and controlled use of models, prompts, retrieval sources, and agent tools; maintain clear accountability boundaries between platform governance and scientific ownership of model behavior.
Define domain-aligned data products and curated datasets for pharmacovigilance (signal detection, case analytics, predictive safety) with clear quality, reliability, and inspection-readiness criteria.
Own target-state and transitional architectures across ingestion, transformation, storage, serving, and consumption on GCP (e.g., BigQuery, Dataform, Cloud Storage); drive reuse via reference architectures and patterns.
Set guardrails for AI/ML and GenAI integrations (embeddings, vector stores, semantic retrieval, RAG) with emphasis on explainability, traceability, and responsible AI; partner with SA Data Scientists without overlapping model development.
Establish canonical data models, data contracts, and lifecycle practices; implement contract-first integration, schema versioning, and controlled interface evolution across producers/consumers.
Chair design reviews; approve solution designs and enforce non-functional requirements (resilience, scalability, security, observability, SLOs); remove delivery blockers and ensure quality and compliance.
Drive data quality, governance, and observability, including validation standards, lineage/metadata, privacy and security controls (least privilege, data minimization, PII/PHI protections), and clear R&D vs. production pathways.
Define standards for APIs, microservices, and retrieval services on GCP (e.g., Cloud Run, GKE); establish reliability and security baselines (SLO/SLA targets, error budgets, zero trust, secrets management, telemetry).
Promote event-driven and streaming architectures (e.g., Pub/Sub, Dataflow) with contract-first integration, backward-compatible evolution, and robust monitoring.
Partner with SA Data Scientists and MLOps to define contract-first model and inference interfaces (batch/online), including rate limits, cost controls, telemetry, and audit logging; SA Data Scientists retain ownership of prompt design and model behavior.
Govern CI/CD for data pipelines and analytics/retrieval services; embed policy-as-code, testing, artifact integrity, and promotion gates; own cost governance (budgets, showback/chargeback, efficiency targets, right-sizing, usage policies).
Coordinate Principal-level engineers’ scope and priorities across pipelines, services, feature stores, and AI/ML integrations; manage cross-team dependencies; communicate decisions to technical and non-technical audiences; mentor teams and uplift standards.
Hands-on (selective): Deliver and maintain reference implementations and design spikes (e.g., ingestion to BigQuery, contract-first schemas, Cloud Run service scaffolds, Pub/Sub/Dataflow patterns) to de-risk delivery and accelerate adoption.

Required

10+ years in data/analytics engineering and architecture, including 3+ years in solution/enterprise architecture roles.
Demonstrated leadership coordinating Principal/Senior engineers and cross-functional teams in regulated environments.
Deep architecture experience on GCP: BigQuery, Dataform, Cloud Storage; orchestration and automation; familiarity with Pub/Sub, Dataflow; services on Cloud Run and/or GKE.
Strong data modeling for analytics and ML (batch and streaming), performance optimization, and observability practices.
Proven experience implementing data contracts, validation, schema versioning, lineage/metadata, and access control.
Hands-on understanding of AI/ML and GenAI patterns for analytics (feature engineering, vector stores, semantic retrieval, RAG) with emphasis on explainability and controls; partner with SA Data Scientists without owning model development.
GxP/CSV/CSA experience for data and analytics platforms; audit readiness and change control.
Excellent communication and stakeholder management; ability to simplify complex topics and influence senior leaders.

Preferred

Master’s degree in Computer Science, Engineering, or related field (or equivalent experience).
Experience in pharmaceuticals, life sciences, healthcare, or related regulated domains.
Experience with Terraform (Infrastructure as Code) and CI/CD; policy-as-code.
Exposure to feature store enablement and MLOps on GCP; familiarity with Vertex AI a plus.
Certifications: Google Professional Cloud Architect or Professional Data Engineer; TOGAF; SAFe
FinOps experience, including budget management and efficiency tracking for cloud analytics workloads.

Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.

Johnson & Johnson is committed to providing an interview process that is inclusive of our applicants’ needs. If you are an individual with a disability and would like to request an accommodation, external applicants please contact us via https://www.jnj.com/contact-us/careers , internal employees contact AskGS to be directed to your accommodation resource.

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Required Skills:

Preferred Skills:

Advanced Analytics, Consulting, Critical Thinking, Data Analysis, Data Privacy Standards, Data Quality, Data Reporting, Data Savvy, Data Science, Data Visualization, Digital Fluency, Econometric Models, Mentorship, Strategic Thinking, Tactical Planning, Technical Credibility

The anticipated base pay range for this position is :

$137,000.00 - $235,750.00

Additional Description for Pay Transparency:

Subject to the terms of their respective plans, employees are eligible to participate in the Company’s consolidated retirement plan (pension) and savings plan (401(k)).

This position is eligible to participate in the Company’s long-term incentive program.

Subject to the terms of their respective policies and date of hire, employees are eligible for the following time off benefits:

Vacation –120 hours per calendar year

Sick time - 40 hours per calendar year; for employees who reside in the State of Colorado –48 hours per calendar year; for employees who reside in the State of Washington –56 hours per calendar year

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 the birth/adoption/foster care of a child

Bereavement Leave – 240 hours for an immediate family member: 40 hours for an extended family member per calendar year

Caregiver Leave – 80 hours in a 52-week rolling period10 days

Volunteer Leave – 32 hours per calendar year

Military Spouse Time-Off – 80 hours per calendar year

For additional general information on Company benefits, please go to: - https://www.careers.jnj.com/employee-benefits

How we rate this

Associate Director, Safety Data Solutions Architect at Johnson & Johnson rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Associate Director, Safety Data Solutions Architect is an open job at Johnson & Johnson.
Level rates this role AI Level 3 of 4: Works on AI.
The listed salary is $137k-$236k a year.
The role is based in Horsham, Pennsylvania, United States of America.
The job was posted on October 27, 2026.
Seniority: executive.
Applications are handled by Johnson & Johnson. Apply on Johnson & Johnson

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Prompt engineeringRAGML OpsAI SafetyVertex AI

Also common in solutions architect jobs at this level

AWS Python Azure Machine learning SQL Kubernetes

Pay

This job starts at: $137k
Typical solutions architect job: $168k

This posting starts 18% below the typical solutions architect job. See solutions architect jobs

Questions you could be asked

How do you structure and test a prompt to get consistent output from a language model?
How would you design a retrieval step so the model answers from real data instead of guessing?
How do you monitor a model once it's live, and how do you know it needs retraining?
How do you think about the risk of an AI system in this kind of role failing silently?
Walk me through how you've used Vertex AI in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Prompt engineering, RAG, ML Ops, AI Safety, and Vertex AI. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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