Description
We are looking for a Senior Agentic AI Engineer to design, develop, and deploy enterprise-grade AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and multi-agent architectures. The ideal candidate will have strong Python development skills and hands-on experience building scalable, secure, and production-ready AI applications, intelligent assistants, and AI-driven automation solutions.
Responsibilities
•Design, develop, and deploy Agentic AI applications using LLMs, RAG, embeddings, vector databases, and multi-agent systems.
•Build and optimize AI workflows and orchestration pipelines using LangChain, LlamaIndex, and other relevant AI frameworks.
•Integrate LLMs and enterprise AI services, including Azure OpenAI or equivalent cloud-based AI platforms.
•Design and implement scalable AI and data pipelines using Azure or AWS cloud services.
•Develop data processing and orchestration workflows using Databricks, Apache Spark, and Apache Airflow.
•Implement MLOps practices for model deployment, monitoring, evaluation, performance optimization, and retraining.
•Containerize and deploy AI applications using Docker and Kubernetes.
•Implement CI/CD pipelines to automate testing, deployment, and release processes.
•Ensure AI solutions meet enterprise requirements for security, governance, scalability, reliability, and performance.
•Collaborate with business stakeholders, data engineers, software developers, and cloud teams to translate business requirements into practical AI solutions.
•Troubleshoot and optimize AI applications for accuracy, latency, cost, and production stability.
Requirements
•8–10 years of overall experience in Software Engineering, Data Engineering, AI Engineering, or a related technical field.
•Strong hands-on programming experience in Python and SQL.
•Practical experience developing Agentic AI applications and LLM-powered solutions.
•Strong understanding of Retrieval-Augmented Generation (RAG), embeddings, semantic search, and vector databases.
•Experience designing or implementing multi-agent systems and AI workflow orchestration.
•Hands-on experience with LangChain, LlamaIndex, Azure OpenAI, or equivalent LLM frameworks and services.
•Experience building scalable AI or data pipelines on Azure or AWS.
•Knowledge of Databricks, Apache Spark, and Apache Airflow.
•Experience with Docker, Kubernetes, and CI/CD pipelines.
•Understanding of MLOps, model evaluation, monitoring, deployment, and lifecycle management.
•Ability to build secure, scalable, maintainable, and production-ready AI solutions.
•Experience working in Agile development environments.
Nice to have
•Experience deploying enterprise-grade AI assistants and intelligent automation solutions.
•Knowledge of advanced agent orchestration patterns, tool calling, function calling, and agent-to-agent communication.
•Experience with hybrid search, reranking, vector search optimization, and enterprise knowledge retrieval.
•Understanding of responsible AI, LLM security, prompt injection mitigation, data privacy, and AI governance.
•Experience with automated evaluation frameworks for LLM and RAG applications.
•Familiarity with infrastructure as code and cloud-native deployment practices.
•Experience optimizing LLM inference performance, latency, and token consumption.
Conditions
Not specified in the posting.
