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Responsible for designing, developing, and deploying AI-driven agentic systems that enable autonomous decision-making, multi-agent collaboration, and scalable AI workflows.
The role focuses on building intelligent backend systems using LLM frameworks and cloud-native architectures.
Key Responsibilities:
• Develop RESTful APIs (FastAPI/Flask) for AI and agent-based systems •
Design and implement agentic workflows using frameworks like LangChain, LangGraph, or similar •
Integrate LLMs with enterprise systems for contextual and intelligent automation • Build and manage
multi-agent orchestration systems and pipelines • Optimize performance and scalability of AI backend
services • Implement authentication, logging, and observability • Deploy solutions on GCP using GKE,
Cloud Run, and Vertex AI • Ensure security and compliance standards for AI workloads • Implement
CI/CD pipelines for AI applications
Required Skills: • Strong experience in Python and backend development • Hands-on with LLM
frameworks: LangChain, LangGraph, HuggingFace • Experience with agent-based architectures and
RAG implementations • Knowledge of Google Cloud Platform (Vertex AI, GKE, Cloud Run) • Familiarity
with MCP servers and A2A communication models • Experience in databases: PostgreSQL, MongoDB,
Redis, FAISS • Understanding of observability tools like Prometheus and Grafana
Preferred Skills:
• Experience with EasyRAG or Google ADK • Exposure to Streamlit UI for AI apps •
Knowledge of Terraform and CI/CD automation • Experience with Kubernetes-based deployments
Qualifications: Bachelor's or Master’s degree in Computer Science, AI, or related field with 5+ years of experience in software development and AI engineering
Benefits
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