Description

You will design and implement GenAI-ready data infrastructure and ML lifecycle pipelines on GCP.

This role is on-site.

Responsibilities

• Design end-to-end data infrastructure on GCP including ingestion via Dataflow and Pub/Sub, BigQuery storage, and vector search platforms.
• Lead deployment of Vertex AI pipelines, covering model training, versioning, CI/CD, experiment tracking, and monitoring.
• Integrate LLMs and generative models using frameworks such as LangChain, AutoGen, CrewAI, MetaGPT, or ADK.
• Implement MLOps and LLMops workflows using Terraform or Cloud Deployment Manager to manage model drift, scaling, and fine-tuning.
• Manage production observability and optimization for agentic AI constructs and vector search engines.

Required Skills

• 5+ years of relevant experience.
• Expertise in GCP services including BigQuery, Dataflow, and Pub/Sub.
• Experience with the Vertex AI ecosystem (Pipelines, Matching Engine, Model Monitoring, Explainable AI).
• Hands-on experience with vector search platforms such as Vertex AI Matching Engine, Pinecone, or FAISS.
• Proficiency in implementing agentic AI via LangChain, AutoGen, CrewAI, MetaGPT, or ADK.
• Knowledge of LLMs, PaLM/Gemini, GANs, and diffusion models.
• Experience with IaC tools like Terraform or Cloud Deployment Manager.
• Strong understanding of CI/CD and MLOps/LLMops lifecycles.

Preferred Skills

• Experience with continuous fine-tuning and scaling production AI models.

Key Skills

Education

Any Gradute