Data and Generative AI Engineer

Johnson & Johnson Johnson & Johnson · Pharma · Raritan, NJ +2

Data and Generative AI Engineer at Johnson & Johnson focused on designing, developing, and delivering Generative/Agentic AI solutions to accelerate End-to-End Data Pipeline Engineering. The role involves building agent workflows, prompt engineering, and integrating LLM APIs, while also handling data ingestion, transformation, and storage. Requires strong Python, software development, data engineering, and cloud skills, with familiarity in LLMs, RAG, and agentic architectures.

What you'd actually do

  1. Design, develop, and maintain software solutions for the Data Technology Team.
  2. Collaborate with multi-functional teams to define, design, and ship new features.
  3. Implement data ingestion, transformation, and storage processes using tools equivalent to Databricks.
  4. Ensure data quality and integrity through meticulous testing and validation, applying Intelligent Automation principles for development, testing and release.
  5. Monitor system performance and solving issues to ensure optimal operation in line with expected SLAs.

Skills

Required

  • Python
  • Software development
  • Data engineering
  • Cloud technologies
  • Familiarity with large language models and generative AI concepts
  • Practical experience calling LLM APIs
  • Basic understanding of agentic architectures
  • Hands-on experience building simple agent workflows or prototypes using an agent framework
  • Competence in prompt engineering for multi-step tasks
  • Awareness of common failure modes for agents and strategies to mitigate them
  • Knowledge of Big Data, Data Pipelining, Machine Learning
  • Ability to connect and partner with various team members
  • Experience in handling compliance consistency, risk management and stakeholder commitments in large organizations.
  • Shown experience in software development, with a focus on and data engineering and cloud technologies.
  • Familiarity with Databricks & Lakehouse Architecture
  • Familiarity with cloud platforms, AWS and Azure Cloud.
  • Strong understanding of data modeling, ETL processes, and data warehousing concepts.

Nice to have

  • Master’s degree or equivalent experience in a relevant field is preferred.

What the JD emphasized

  • Minimum of 4 years of relevant experience in an industry setting is required.
  • Minimum of a Bachelors degree or equivalent experience is required, preferably in Computer Science, Engineering, Data Science, Business Analytics, Science, any STEM field, Engineering or any other quantitative or STEM field.

Other signals

  • Design, develop and deliver Generative/Agentic AI solutions that accelerate End-to-End Data Pipeline Engineering activities.
  • Hands-on experience building simple agent workflows or prototypes using an agent framework (e.g., LangChain, LlamaIndex, Haystack) or equivalent libraries.
  • Competence in prompt engineering for multi-step tasks and chaining prompts to implement simple planning/execution logic.