We are seeking a highly skilled Agentic AI Engineer to design, develop, and deploy autonomous AI agents and workflows within the Google Cloud Platform (GCP) ecosystem. The ideal candidate will have hands-on expertise in building multi-agent AI systems, integrating LLMs (such as Gemini, GPT, or Claude), and orchestrating intelligent pipelines that leverage GCP services for scalability, observability, and security.
This role requires a deep understanding of AI architecture, vector search, orchestration frameworks, and event-driven cloud systems . You will collaborate with data engineers, MLOps teams, and solution architects to deliver real-world AI capabilities that adapt, reason, and act autonomously.
Key Responsibilities
Agentic AI & LLM Integration
- Design and implement autonomous AI agents capable of reasoning, planning, and executing workflows using LLMs (Gemini, GPT, Claude, etc.).
- Implement multi-agent coordination frameworks (e.g., LangChain, CrewAI, AutoGen, or Semantic Kernel).
- Build adaptive memory systems and contextual knowledge retrieval pipelines using Vertex AI , BigQuery , and GCP Vector Search .
- Integrate with external APIs and enterprise systems using secure, event-driven architectures.
GCP Cloud Engineering
Develop and deploy AI workloads in GCP leveraging :Vertex AI , Pub / Sub , Cloud Run , Cloud Functions , and BigQuery .GCS for storage and Cloud Composer (Airflow) for orchestration.Build containerized microservices (Docker / Kubernetes / GKE) for scalable AI workflows.Implement CI / CD pipelines using Cloud Build or GitHub Actions for rapid iteration.Data & Intelligence Layer
Architect retrieval-augmented generation (RAG) pipelines using GCP Vector Search , Pinecone , or Weaviate .Connect unstructured and structured data sources to LLMs using Dataform , BigQuery , and Vertex AI Matching Engine .Design prompt optimization, context management, and long-term memory storage strategies.Security, Governance, and Observability
Enforce IAM, service accounts, and least-privilege policies across agent workflows.Integrate Cloud Logging , Cloud Monitoring , and Dynatrace (if applicable) for full observability of agent actions.Implement data governance and compliance standards for AI model usage and external API calls.Innovation & Collaboration
Partner with product, ML, and software teams to define use cases for agentic automation.Continuously evaluate emerging frameworks for multi-agent systems and adaptive reasoning.Contribute to architectural roadmaps, PoCs, and AI innovation initiatives within the organization.Qualifications
Bachelors or Masters degree in Computer Science, Data Science, or related field.5+ years of experience in cloud-based development (GCP preferred).3+ years of experience with LLM-based applications (LangChain, LlamaIndex, or OpenAI APIs).Strong programming skills in Python, Go, or Node.js .Experience with RAG , vector databases , and agent orchestration frameworks .Familiarity with Vertex AI , GKE , Pub / Sub , BigQuery , and Cloud Functions .Solid understanding of MLOps , microservices , and event-driven design .Preferred Skills
Experience with Google Gemini API or other advanced foundation models.Knowledge of Autonomous AI frameworks (e.g., AutoGPT, BabyAGI, CrewAI).Exposure to LangGraph or Semantic Kernel for graph-based agent design.Experience integrating AI observability tools (Weights & Biases, Arize AI, or Vertex AI Model Monitoring).Understanding of RAG governance , compliance, and cost optimization strategies.