System Soft Technologies

Johnson & Johnson is a leading global healthcare company.

GenAI Operations / Technical Lead

Location

India

Posted

2 days ago

Salary

0

Seniority

Lead

No structured requirement data.

Job Description

GenAI Operations / Technical Lead

System Soft Technologies

Role Description Client in the pharmaceutical industry is seeking a GenAI Operations / Technical Lead to lead the design, deployment, and operational support of enterprise-scale Generative AI solutions. This is a hands-on technical leadership role focused on building scalable, production-ready GenAI applications that improve business efficiency across the organization. The ideal candidate has deep experience deploying GenAI applications in enterprise environments, with expertise in agentic AI, cloud platforms, and GenAI operations, including monitoring, testing, and production support. - Lead the architecture, deployment, and operational support of enterprise GenAI applications. - Build and maintain AI solutions leveraging the latest LLM and agentic AI capabilities. - Design agentic workflows using LangGraph and/or LangChain. - Establish best practices for GenAI operations, including monitoring, testing, evaluation, and observability. - Integrate structured and unstructured data from platforms such as SharePoint, Databricks, and Snowflake. - Ensure AI solutions are scalable, reliable, and production ready. - Provide hands-on technical leadership across multiple AI initiatives. Qualifications - Experience leading the technical delivery of enterprise GenAI applications. - Strong hands-on experience with production LLM applications. - AWS expertise is required; experience with Azure is preferred, and GCP is a plus. - Experience with LangGraph and/or LangChain. - Experience with GenAI monitoring, testing, evaluation, and production support. - Experience working with structured and unstructured enterprise data. - Strong Python and software engineering skills. - Experience in large enterprise environments. Requirements - Experience with RAG architectures and vector databases. - Familiarity with MLOps, CI/CD, and containerized deployments. - Multi-cloud experience across AWS, Azure, and GCP.

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