Description

You will design and deploy Generative AI and MLOps solutions to address complex business challenges and optimize enterprise workflows.

This role is hybrid.

Responsibilities

• Design, build, and deploy GenAI solutions using Retrieval Augmented Generation (RAG) and Model Context Protocol (MCP).
• Implement and manage Vector Databases such as Pinecone, Weaviate, or Milvus for semantic search.
• Develop models to detect and predict anomalies in workflows and system performance using operational data.
• Build AI components for the Pega platform, including automated code review tools.
• Apply AI to analyze release management issues and predict software release risks.

Required Skills

• 7–10 years of overall professional experience, including 3–4 years focused on AI, ML, and data science.
• Hands-on experience with Generative AI, RAG systems, and AI agent frameworks like LangChain, LangFlow, or Crew AI.
• Proficiency in Python, PyTorch, TensorFlow, and various ML frameworks.
• Practical experience with MLOps, DevOps, and cloud platforms including AWS, Azure, or GCP.
• Experience with Vector Databases and Model Context Protocol (MCP).
• Familiarity with operational data tools such as New Relic or Kibana.
• Strong problem-solving abilities and the ability to communicate technical concepts to non-technical stakeholders.

Preferred Skills

• Bachelor’s or master’s degree in Computer Science, Data Science, AI/ML, or a related field.
• Development experience in Java or Pega and knowledge of the Pega platform.

Key Skills

Education

Any Graduate