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…