Senior Data & Applied AI Engineer

About the role

Johnson & Johnson is seeking a highly skilled Senior Data & Applied AI Engineer to design, build, and scale enterprise data products, AI solutions, and MLOps platforms. The role involves leading the development of reliable data pipelines, reusable data products, and AI-enabled services within a secure, scalable enterprise environment.

Key responsibilities

• Design, build, and optimize batch and streaming data pipelines using Databricks, PySpark, SQL, Azure Data Factory, and Azure cloud services.
• Develop reusable, governed data products and analytical datasets for reporting, advanced analytics, and AI use cases.
• Implement AI and Generative AI solutions, including retrieval, orchestration, evaluation, integration, and production operationalization.
• Build and operate MLOps capabilities for model development, deployment, monitoring, lineage, governance, and lifecycle management.
• Create cloud‑native platform services, micro‑services, REST APIs, and event‑driven components that expose data and AI capabilities.
• Develop full‑stack applications using TypeScript, React, Node.js, and related technologies to operationalize data and AI solutions.
• Establish CI/CD pipelines, DevOps automation, GitOps workflows, and infrastructure‑as‑code solutions.
• Implement security controls, observability, and performance monitoring across data pipelines, AI services, and infrastructure.

Required profile

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science or related field.
• 6+ years of engineering experience delivering enterprise‑scale data, AI, analytics, or cloud platforms.
• Strong technical leadership, stakeholder management, and mentoring abilities.
• Experience working with offshore teams and managing SOWs and resource planning.

Required skills

• Python, PySpark, SQL
• Databricks, Azure Data Factory, Azure cloud data services
• MLOps tools (MLflow, ZenML) and model lifecycle management
• Docker, Kubernetes (AKS preferred)
• Cloud‑native architecture, CI/CD, infrastructure automation
• REST API design, TypeScript, React, Node.js
• Observability platforms (OpenTelemetry, Grafana, Prometheus, Azure Monitor)
• GitOps practices (ArgoCD or similar)