Director, Enterprise Observability and Automation

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:

Technology Product & Platform Management

Job Sub Function:

Technical Product Management

Job Category:

People Leader

All Job Posting Locations:

Raritan, New Jersey, United States of America, Singapore, Singapore

Job Description:

An internal pre-identified candidate for consideration has been identified. However, all applications will be considered.

Key Responsibilities

Primary Responsibilities

Enterprise Observability Strategy: Define and execute a multi-year enterprise observability and automation strategy aligned with J&J Technology priorities, business outcomes, cybersecurity expectations, and the needs of Innovative Medicine, MedTech, and enterprise functions.

Architecture and Telemetry: Define a vendor-neutral target architecture spanning telemetry collectors, agents, gateways, routing, processing, and backend platforms.

Observability Data Strategy: Establish standards for data models, tagging and metadata, retention tiers, data residency, personally identifiable information handling, and cross-signal correlation.

AI and AIOps: Establish lifecycle monitoring for AI, machine-learning, and agentic solutions, including performance, drift, latency, cost, quality, explainability, bias, safety signals, and human oversight.

Intelligent Operations: Advance anomaly detection, intelligent alerting, event correlation, automated root-cause analysis, predictive operations, and remediation to reduce operational noise and improve resilience.

Service Reliability: Partner with product, platform, and business technology leaders to establish service-level objectives, service-level indicators, error budgets, and experience measures for critical products and services.

Portfolio and Vendor Management: Own the enterprise observability architecture, standards, roadmap, investment portfolio, and strategic vendor relationships across metrics, logs, traces, events, and digital experience telemetry.

Governance and Risk: Collaborate with Information Security & Risk Management, privacy, quality, regulatory, legal, data, and responsible-AI partners to embed practical controls that support security, compliance, fairness, responsibility, and transparency.

People Leadership: Build, lead, and develop high-performing teams spanning observability engineering, site reliability engineering, AI/ML platform engineering, and AIOps while fostering inclusion, accountability, and talent growth.

Secondary Responsibilities

Operational Resilience: Strengthen incident, problem, change, and knowledge-management practices through effective on-call operations, post-incident reviews, actionable problem management, and continuous learning.

Executive Reporting: Provide leadership with clear insight into service health, AI performance, reliability risk, adoption, value realization, and investment priorities.

Continuous Improvement: Drive simplification, interoperability, reuse, cost optimization, automation adoption, and measurable improvements in operational maturity.

Required Qualifications & Skills

Experience

Bachelor's degree in computer science, engineering, information systems, or a related field; an advanced degree is preferred.

10+ years of progressive experience in software engineering, platform engineering, site reliability engineering, enterprise operations, or a related technology discipline.

4+ years of experience leading teams and/or people leaders in a global, matrixed environment.

Demonstrated experience defining and implementing enterprise-scale observability strategies across business-critical applications and services.

Proven experience implementing operational automation, orchestration, AIOps, or AI-driven solutions.

Experience improving reliability, reducing mean time to detect and restore, simplifying tool landscapes, and optimizing technology spend.

Experience working in a highly regulated environment and translating security, privacy, quality, and compliance expectations into practical engineering controls.

Technical Skills

Expertise in OpenTelemetry, distributed tracing, metrics, logs, events, digital experience monitoring, and large-scale telemetry pipelines.

Strong knowledge of cloud-native architecture, public cloud platforms, Kubernetes, APIs, microservices, and modern software delivery practices.

Experience operating AI/ML or large-language-model solutions in production, including evaluation, monitoring, MLOps/LLMOps, guardrails, and model-risk controls.

Experience with observability and monitoring platforms such as Splunk, AppDynamics, Grafana, Telegraph, Clickhouse,cloud-native monitoring, or comparable technologies.

Strong understanding of Incident, Problem, Change, and Knowledge Management processes and their integration with enterprise observability and automation.

Leadership & Collaboration

Exceptional communication, documentation, and stakeholder-management skills, with the ability to translate technical complexity into risk, value, investment, and business decisions for senior leaders.

Ability to lead through critical incidents, service disruption, ambiguity, and competing enterprise priorities.

Strong analytical, problem-solving, and continuous-improvement mindset.

Demonstrated commitment to inclusive leadership, talent development, collaboration, and Our Credo values.

Preferred Qualifications

Experience with LLM observability, evaluation frameworks, agentic-AI runtime controls, retrieval-augmented generation, and AI guardrails.

Familiarity with responsible-AI frameworks and evolving regulations and standards, including NIST AI RMF and the EU AI Act.

Experience managing large technology portfolios, enterprise observability spend, and strategic suppliers.

Experience in healthcare, life sciences, medical technology, or another quality- and compliance-intensive industry.

Relevant certifications in ITIL, Splunk, ServiceNow, cloud platforms, AI, machine learning, data analytics, or automation.

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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.

Required Skills:

Preferred Skills:

Consistency, Creating Purpose, Developing Others, Green Manufacturing, Human-Computer Interaction (HCI), Inclusive Leadership, Leadership, People Performance Management, Process Control, Product Development Lifecycle, Product Reliabilit