Role Description As a Full Stack Agentic AI Solution Developer you will be responsible for designing, developing, and deploying end-to-end agentic AI systems that are intelligent, autonomous solutions. This role combines AI engineering, software development, and system integration expertise to build scalable, production-ready solutions leveraging LLMs, vector databases, orchestration frameworks, and modern web technologies. You will work closely with data scientists, backend engineers, and product teams to create self-directed AI agents capable of handling complex tasks such as workflow automation, knowledge retrieval, and multi-step reasoning. In this role you will play a key role in: - GenAI & Multi-Agent Engineering: - Architect and implement multi-agent orchestration frameworks using GenAI models (e.g., Gemini, Claude, LLaMA, Mistral). - Develop agent roles, memory systems, and inter-agent communication protocols. - Integrate open-source orchestration platforms (LangChain, CrewAI, AutoGen) or Google. - Work with Cloud tools (Vertex AI, Agent Builder) and optimize agent workflows for reasoning, planning, and tool use. - Prompt Engineering: - Design and iterate high-quality prompts for agentic tasks. - Implement prompt templates, context windows, and RAG pipelines using vector databases (e.g., FAISS, Pinecone, Weaviate). - Evaluate prompt performance and fine-tune for accuracy, latency, and cost. - Backend Web Development: - Build and maintain backend services and RESTful APIs to support agent orchestration and user interfaces. - Develop microservices using Python (FastAPI, Flask) or Node.js, and deploy on GCP (Cloud Run, App Engine, Kubernetes). - Ensure backend scalability, security, and integration with cloud-native services (BigQuery, Pub/Sub, Firestore). - Cloud & DevOps: - Deploy and monitor GenAI applications on Google Cloud Platform using CI/CD pipelines. - Manage infrastructure-as-code (Terraform, Cloud Build) and containerization (Docker, Kubernetes). - Implement logging, tracing, and performance monitoring for agent systems. Qualifications - Experience in the programming languages SQL & Python. - Experience with GenAI frameworks (LangChain, LangGraph, Hugging Face, OpenAI API). - Solid understanding of LLM orchestration, prompt engineering, and agentic workflows. - Experience with backend frameworks (FastAPI, Flask, Node.js) and cloud deployment. - Experience with Vertex AI, Agent Builder, Google ADK and Google Cloud Functions. - Understanding of frontend frameworks (React, Next.js) and backend frameworks (FastAPI, Flask, Node.js) and cloud deployment. - Knowledge of cloud platforms (AWS Sagemaker, Azure AI, or GCP Vertex AI). - If you also have familiarity with vector databases, RAG, and LLM evaluation techniques, that’s even better! Benefits - Flexible work arrangements to maintain a healthy work-life balance. - Career growth programs and diverse professions to explore a world of opportunities. - Partnerships with companies like Google, Microsoft, Amazon, and Databricks for valuable certifications in the latest technologies. Application As part of our recruitment process, identity verification will be conducted through inspection of your ID card, and background checks may be carried out as required.