Description:

About the Role

We are seeking a highly skilled AI Engineer with hands-on experience in building Generative AI (GenAI) and Large Language Model (LLM) applications on Google Cloud.

In this role, you will design, develop, and deploy scalable, production-grade AI solutions using Vertex AI and Gemini models for enterprise clients across industries.

You will work closely with product teams, cloud architects, and client stakeholders to translate business requirements into intelligent, reliable AI-powered systems.

Key Responsibilities:

- Design, build, and deploy GenAI and LLM-based applications on Google Cloud Platform (GCP)

- Develop conversational AI, intelligent search, and RAG-based systems using Vertex AI

- Implement document understanding and data extraction workflows using Document AI

- Build semantic search and retrieval pipelines using Embeddings and Vector Search

- Integrate enterprise data sources and enable grounding using Google Search and internal datasets

- Optimize prompts, workflows, and model responses for accuracy, latency, and cost

- Collaborate with cross-functional teams to deliver end-to-end AI solutions

- Create clear technical documentation and support client-facing discussions

Technical Skills (Any 68 Required):

- Vertex AI Agent Builder for conversational AI and enterprise search

- Gemini models (Pro, Flash, Ultra) via Vertex AI APIs

- Vertex AI Search and Conversation for RAG implementations

- Document AI for structured data extraction from unstructured documents

- Vertex AI Embeddings and Vector Search for semantic retrieval

- Grounding techniques using Google Search and enterprise data sources

- LangChain and Vertex AI SDK (Python)

- Prompt engineering, function calling, tool use, and multi-modal AI patterns

Experience & Qualifications:

- 3+ years of experience in AI/ML engineering

- At least 1 year of hands-on experience with Google Cloud AI services

- Delivered 2+ production-grade AI solutions (e.g., chatbots, document processing systems, intelligent search)

- Strong problem-solving and system design skills

- Excellent communication skills for client interactions and technical documentation

Nice to Have:

- Experience deploying AI systems in regulated or enterprise environments

- Familiarity with MLOps, CI/CD, and cloud security best practices

- Exposure to cost optimization and performance tuning for GenAI workloads