Gen AI Developer

Role & responsibilities

Job Summary

We are looking for an experienced Gen AI Developer with strong hands-on expertise in Google Cloud Platform (GCP), Generative AI, Large Language Models (LLMs), and Model Context Protocol (MCP). The ideal candidate will design and develop scalable AI-powered applications, intelligent agents, and enterprise GenAI solutions using GCP services.

Key Responsibilities

• Design, develop, and deploy Generative AI and LLM-based applications on GCP.
• Build and integrate MCP servers, MCP clients, tools, and workflows using the Model Context Protocol.
• Develop AI agents and agentic workflows capable of tool calling and enterprise system integration.
• Work with Google Vertex AI, Gemini models, and other GCP AI/ML services.
• Develop RAG (Retrieval-Augmented Generation) solutions using enterprise data sources.
• Build APIs and backend services using Python and relevant GenAI frameworks.
• Integrate LLM applications with databases, APIs, enterprise applications, and external tools.
• Implement prompt engineering, evaluation, guardrails, observability, and optimization for GenAI applications.
• Deploy and manage AI solutions using GCP cloud-native services.
• Collaborate with data scientists, software engineers, architects, and business teams to deliver production-ready AI solutions.
• Ensure solutions meet requirements for security, scalability, performance, and reliability.

Required Skills

• Strong hands-on experience in Generative AI / GenAI development.
• Strong programming experience in Python.
• Hands-on experience with GCP / Google Cloud Platform.
• Experience with Vertex AI and/or Gemini.
• Strong understanding of LLMs, Prompt Engineering, RAG, embeddings, vector databases, and AI agents.
• Hands-on experience with MCP (Model Context Protocol) and MCP-based integrations.
• Experience developing or integrating MCP servers/tools.
• Experience with REST APIs, microservices, and system integrations.
• Knowledge of cloud deployment, CI/CD, containers, and Git.

Good to Have

• Experience with LangChain, LangGraph, LlamaIndex, or similar GenAI frameworks.
• Experience with BigQuery, Cloud Run, GKE, Cloud Functions, Pub/Sub, and Cloud Storage.
• Experience with vector databases such as Vertex AI Vector Search, Pinecone, Weaviate, or FAISS.
• Knowledge of GenAI security, responsible AI, and LLM evaluation.
• Experience with agentic AI architectures and multi-agent systems.

Preferred candidate profile