We are seeking an experienced hands-on Generative AI Architect to lead the design and delivery of cutting-edge AI solutions using Google Cloud Platform. The ideal candidate will have deep experience in LLM-based architectures, multi-agent systems, Retrieval-Augmented Generation (RAG), and agentic RAG frameworks. You will partner with data scientists, ML engineers, product teams, and platform engineers to design and deploy scalable and secure GenAI solutions.
Key Responsibilities:
- Architect and deliver LLM-powered multi-agent systems on GCP tailored for enterprise use cases.
- Design and implement Multi-Agentic workflows, RAG, and agentic RAG solutions leveraging ADK, A2A, AgentSpace, including integrating Agents built on other frameworks like LangChain, LangGraph, Autogen, CrewAI
- Drive end-to-end solution design, including data ingestion, preprocessing, embeddings, vector stores, orchestration, and serving.
- Good understanding of VertexAI search and vector databases (AlloyDB) and their usage.
- Hands-on experience on frameworks like Langchain/LangGraph/CrewAI/AutoGen
- Build and operationalize prompt engineering frameworks, tool-using agents, and context-aware agents.
- Could you collaborate with stakeholders to understand business requirements and map them to GenAI capabilities
- Integrate GenAI systems with enterprise data lakes/warehouses.
- Ensure production readiness via monitoring, CI/CD pipelines, prompt testing, and evaluation metrics.
- Conduct POCs and research on emerging GenAI tech stack
- Mentor teams on GCP AI stack, best practices, responsible AI principles, and LLMOps.
Must-Have Skills:
Generative AI Expertise
- Good understanding of LLM architectures (transformers, attention mechanisms).
- Experience with multi-agent systems, autonomous agents, and tool orchestration.
- Proven track record with Multi-Agentic Workflows, Retrieval-Augmented Generation (RAG), and Agentic RAG implementations.
- Experience building chatbots, Natural Language to SQL, or semantic search over enterprise data.
- Hands-on with LLM APIs (Vertex AI Gemini, Anthropic, Models available in Vertex AI Model Garden).
- Prompt engineering (zero-, one-, few-shot), prompt templating, and evaluation.
- Monitoring, evaluation, and feedback loops for GenAI solutions.
GCP Architecture
- 7+ years of hands-on experience on Google Cloud Platform
- 1-2 years of hands-on GenAI experience on Google Cloud Platform
- Expertise in Vertex AI, BigQuery, GKE, Cloud Storage, Cloud Run, Vector Databases on GCP
- Building and deploying scalable GenAI solutions on GCP
Good-to-Have Skills:
- Experience with fine-tuning LLMs, prompt tuning, or LoRA on Vertex AI.
- Exposure to Generative UI design with tools like React or Streamlit.
- Security, governance, and Responsible AI principles in LLM solutions.
- Experience in Document parsing (e.g., Document AI).
- Exposure to multi-modal GenAI (text+vision+audio).
- Understanding of cost optimization and quota management for GenAI workloads on GCP.
