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Job Function:

Technology Product & Platform Management

Job Sub Function:

Software Engineering – Integration

Job Category:

Scientific/Technology

All Job Posting Locations:

Beerse, Antwerp, Belgium, Limerick, Ireland

Job Description:

Johnson & Johnson is recruiting for a Manager - GenAI Engineering & Enablement for the EMEA Full Stack Engineering chapter, located in Beerse, Belgium.

Join our dynamic team as a Manager, GenAI Engineering & Enablement and become the catalyst behind our next wave of innovation. At TS EMEA Full Stack Engineering (FSE), we build modern, secure, and scalable software products for our business partners—and we’re rapidly accelerating the adoption of enterprise GenAI to supercharge developer productivity, speed platform delivery, and enable responsible innovation at scale across EMEA.

In this role, you will support the implementation of the GenAI strategy, platform enablement, and engineering execution that power our products every day. You’ll help apply standards and guardrails that keep us fast and safe, partner closely with the global TS GenAI Platform and XENA Developer Experience teams to champion open collaboration, and uplift engineering teams through targeted training, proven patterns, and reusable assets. From discovery and pilot to productization and scaled adoption, you’ll contribute to successful project delivery—embedding responsible AI across the lifecycle and turning great ideas into resilient, production‑ready solutions.

Bring your expertise, amplify your impact, and help us redefine what’s possible. In a culture where creativity thrives and collaboration is the norm, you’ll streamline how we build, elevate how our teams deliver, and shape the future of our platform and products across EMEA. If you’re ready to lead from the front and transform possibilities into realities, we’d love to have you on the journey.

Key Responsibilities:

• Execute on the defined GenAI strategy and roadmap for TS EMEA Full Stack Engineering, ensuring alignment with enterprise platforms and compliance requirements.

• Ensure adherence to governance practices, including guardrails and usage guidelines, to balance innovation speed with regulatory and policy alignment.

• Translate and embed open collaboration models (e.g., XENA) into GenAI workstreams, fostering clear contribution and decision-making processes.

• Partner with platform engineering to standardise and enhance GenAI platform touchpoints, promoting reusable assets and preventing duplication.

• Develop and curate reference implementations and templates for engineering teams, supporting consistent AI delivery.

• Lead comprehensive GenAI upskilling and training programmes, ensuring inclusive access for all EMEA locations and measuring adoption through objectives and key results.

• Showcase impactful use cases and measurable productivity improvements enabled by GenAI adoption.

• Supervise a portfolio of GenAI initiatives, ensuring secure, privacy-conscious, and responsible AI practices throughout the delivery lifecycle.

• Provide technical guidance and unblock teams on critical GenAI engineering challenges, while coaching tech leads towards self-sufficiency.

• Foster a collaborative community by connecting squads to enterprise communities of practice and encouraging open participation in platform evolution.

Qualifications

Education:

• We expect the candidate to hold an advanced degree (MSc/PhD) in AI/ML, Data Science, Computer Science, or Applied Mathematics.

Experience and Skills:

Required:

• 8+ years in software or platform engineering, with experience in team leadership or project management for modern application delivery.

• Hands‑on familiarity with GenAI/LLM systems in production—including prompting, grounding/RAG, evaluation, safeguards, and telemetry

• Experience with to enterprise AI tooling enablement (e.g., Copilot, Intelligent Chat) and broader developer‑productivity accelerators.

• A deep understanding of DevOps/MLOps for reliability and lifecycle management (CI/CD for models and services, monitoring, rollback, and drift management).

• Knowledgeable in creating playbooks, training programs, office hours, and inner‑source libraries; establishing guardrails for responsible AI use across multiple teams.

• Comfortable operating across product, security, platform, legal/privacy, and domain leadership; able to translate sophisticated AI concepts for executive and non‑technical audiences.

• Proficiency in at least one modern language (e.g., Python, TypeScript/Node.js, ...) to review designs/code and build prototypes using common frameworks (e.g., FastAPI, Flask, Express) when needed.

• Production experience with at least one major cloud (Azure, AWS, or GCP) and container/orchestration stacks (Docker, Kubernetes); familiarity with CI, artifact registries, and basic IaC.

• Excellent problem-solving skills and ability to quickly adapt to new technologies and programming languages.

• Strong communication and collaboration skills, with the ability to work effectively in team environments.

• Fluency in English is required (other languages are beneficial).

Preferred:

• Experience contributing to or stewarding open collaboration models (e.g., open meetings, contributor guides, shared backlogs, decision records/ADRs) and cultivating healthy inner‑source communities.

• Background working with enterprise platforms and regulated environments (e.g., GxP/SaMD), and comfort navigating policy, data protection, and risk frameworks (e.g., GDPR, model risk management).

• Deeper LLMOps capabilities: vector databases and retrieval patterns, prompt/version management, offline & online evaluation frameworks, safety/moderation pipelines, and cost/performance tuning (caching, quantization).

• Observability for AI systems: tracing, evaluation pipelines, feedback loops; familiarity with experiment tracking tools.

• Community building: running CoPs, hackathons, and publishing patterns; recognized internal thought leadership or external speaking/writing.

• Relevant certifications (e.g., Azure AI Engineer, AWS ML Specialty, GCP ML Engineer); privacy/security credentials (e.g., CIPP/E) are beneficial.

Required Skills:

Preferred Skills:

Analytical Reasoning, Coaching, Continuous Integration and Continuous Deployment (CI/CD) Pipeline, Critical Thinking, Human-Computer Interaction (HCI), Information Technology (IT) Infrastructure, Information Technology Strategies, Innovation, Organizing, Presentation Design, Process Improvements, Software Development Management, System Integration, Systems Analysis, Technical Credibility, Technical Writing, Workflow Automation