Posted:5 days ago|
Platform:
On-site
Full Time
Lead Agentic AI Engineer with over 5 years experience to manage AI Engineer Team in the the design, build, and deploy autonomous, goal-driven AI systems using the Google Gemini ecosystem. The ideal candidate will integrate LLM reasoning, memory, and tool orchestration within Vertex AI, leveraging Gemini models to create agentic applications that plan, act, and adapt dynamically.
Key Responsibilities
Design and implement agentic workflows that combine Gemini models with tools, APIs, and external data sources.
Develop multi-agent architectures with planning, reflection, and memory layers using Vertex AI Agents, LangChain, or similar frameworks.
Integrate AI agents into enterprise applications via Vertex AI Extensions, BigQuery, and Cloud Functions.
Ensure governance, observability, and cost optimization within GCP AI workloads.
Must-Have Skills
Prior experience implementing Agentic, GenAI, AI, and ML applications and leading a team of AI/ML Engineers.
Proficiency with Google Cloud Platform (GCP) — especially Vertex AI, Gemini API, and BigQuery.
Strong experience with Python and AI orchestration frameworks (LangChain, AutoGen, or CrewAI).
Deep understanding of LLM prompt engineering, reasoning chains, and tool calling patterns.
Nice-to-Have Skills
Proficiency with Google Cloud Platform (GCP) — especially Vertex AI, Gemini API, Google ADK, and BigQuery ML.
Experience building autonomous agents using Vertex AI Agents, PaLM API, or Gemini SDK strongly preferred
Data Science experience strongly preferred.
Familiarity with retrieval-augmented generation (RAG) pipelines and vector databases (e.g., Pinecone, Weaviate, or Vertex Matching Engine).
Knowledge of MLOps on GCP, including model deployment, monitoring, and CI/CD integration.
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