Description

Build, tune, and deploy production-grade Generative AI and LLM applications.

This role is on-site.

Responsibilities

• Design and implement Retrieval-Augmented Generation (RAG) pipelines with advanced prompt engineering.
• Build and deploy LLM-based applications using Vertex AI and Hugging Face.
• Develop agentic framework use cases and integrate generative AI with enterprise systems.
• Establish MLOps principles, model evaluation metrics, and CI/CD pipelines for automated testing.
• Manage containerized applications using OpenShift or Kubernetes in cloud-native environments.

Required Skills

• 10+ years of experience in Apps Development or Systems Analysis.
• Deep expertise in GenAI, Machine Learning, NLP, Neural Networks, and LLMs (Gemini, Claude, Llama).
• Strong proficiency in Python, including Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Transformers, FastAPI, LangChain, and LlamaIndex.
• Hands-on experience with vector databases (PG Vector, Pinecone, Mongo Atlas, Neo4j) and unstructured data processing.
• Proven track record of deploying GenAI models to production with robust MLOps practices.
• Experience with CI/CD tools: Jenkins, GitLab CI, Azure DevOps, or ArgoCD.
• Knowledge of Guardrails and methodologies for assessing GenAI performance and safety.

Preferred Skills

• Bachelor's degree in Computer Science, Engineering, or related field.
• Experience with knowledge graphs and high-throughput data processing architectures.

Key Skills

Education

Bachelor's degree