Job Description :

We are looking for an experienced Agentic AI Engineer with expertise in designing, developing, and deploying intelligent multi-agent AI solutions. The ideal candidate will have strong hands-on experience with Google Cloud Platform (GCP), Vertex AI, Python, Large Language Models (LLMs), and Agentic AI frameworks, along with a deep understanding of AI orchestration, evaluation, and human-in-the-loop (HITL) systems.

Key Responsibilities :

- Design, develop, and deploy Agentic AI and Multi-Agent Systems for enterprise use cases.

- Build AI applications using Google Agent Development Kit (ADK) or similar agent frameworks.

- Develop and deploy AI solutions on Google Cloud Platform (GCP) using Vertex AI.

- Build LLM-powered applications, AI agents, and workflow orchestration pipelines.

- Implement Human-in-the-Loop (HITL) workflows for reliable and governed AI systems.

- Optimize prompt engineering, reasoning strategies (Chain-of-Thought, ReAct), and AI agent performance.

- Develop scalable backend services and AI workflows using Python.

- Evaluate AI model performance using automated evaluation frameworks, benchmarking, and quality metrics.

- Debug, optimize, and improve LLM responses, latency, reliability, and cost efficiency.

- Collaborate with product, engineering, and business teams to deliver production-ready AI solutions.

- Stay updated with the latest advancements in Generative AI, LLMs, Agentic AI, and Google Cloud technologies.

Required Skills :

- 8 to 10 years of software development experience with strong expertise in Python.

- Hands-on experience building Agentic AI or Multi-Agent Systems.

- Experience with Google Cloud Platform (GCP) and Vertex AI.

- Experience with Google Agent Development Kit (ADK) or similar agent frameworks such as LangGraph, CrewAI, AutoGen, or Semantic Kernel.

- Strong understanding of Large Language Models (LLMs) and Generative AI.

- Experience with AI workflow orchestration, prompt engineering, and reasoning techniques such as Chain-of-Thought (CoT) and ReAct.

- Experience implementing Human-in-the-Loop (HITL) workflows.

- Knowledge of AI evaluation frameworks, benchmarking, debugging, and model optimization.

- Experience integrating AI solutions using REST APIs and cloud services.

- Strong analytical, problem-solving, and communication skills.

Preferred Skills :

- Experience with Retrieval-Augmented Generation (RAG), vector databases, and embeddings.

- Knowledge of ML frameworks such as TensorFlow or PyTorch.

- Experience with Docker, Kubernetes, CI/CD, and MLOps.

- Familiarity with BigQuery, Cloud Functions, Cloud Run, or other GCP services.

- Experience working on enterprise-scale AI applications.