Job Title

Job Title: AI Engineer Experience: 3–5 Years Department: Engineering Employment Type: Full-Time About the Role We are looking for a highly skilled Agentic AI Engineer to design, build, and deploy intelligent AI agents capable of autonomous decision-making and task execution. The ideal candidate will have hands-on experience working with multiple Large Language Models (LLMs), agent frameworks, vector databases, and cloud platforms, along with strong DevOps and production deployment awareness. You will be responsible for building AI-driven systems using agentic architectures, integrating LLMs with tools, APIs, and data sources to create scalable and reliable enterprise AI applications. Key Responsibilities • Design and implement agentic AI architectures for autonomous task execution and decision-making. • Develop and deploy LLM-powered applications and AI agents for real-world business use cases. • Integrate multiple LLM providers (OpenAI, Anthropic, open-source models, etc.) into AI systems. • Build and manage Retrieval-Augmented Generation (RAG) pipelines using vector databases. • Develop solutions using AI frameworks such as Lang Chain, LlamaIndex, Autogen, Crew AI, or similar. • Work with multiple vector databases for semantic search and memory management. • Design multi-agent systems that collaborate to solve complex tasks. • Deploy AI solutions across multi-cloud environments (AWS, Azure, GCP). • Implement CI/CD pipelines, containerization, and infrastructure automation for AI workloads. • Monitor and optimize AI model performance, cost, latency, and reliability. • Collaborate with data engineers, ML engineers, and product teams to deliver AI solutions. • Ensure security, governance, and responsible AI practices. Required Skills • Strong experience with Python and AI/ML development. • Hands-on experience with multiple LLMs (OpenAI, Anthropic, Cohere, Mistral, Llama, etc.). • Experience building agent-based AI systems. • Experience with AI orchestration frameworks (LangChain, LlamaIndex, CrewAI, AutoGen, or similar). • Hands-on experience with vector databases such as Pinecone, Weaviate, Milvus, Chroma, or FAISS. • Experience implementing RAG architecture. • Knowledge of prompt engineering and LLM optimization techniques. • Experience deploying solutions on AWS / Azure / GCP. • Familiarity with Docker, Kubernetes, CI/CD pipelines, and DevOps practices. • Strong understanding of API integration and microservices architectures. Good to Have • Experience with fine-tuning or parameter-efficient tuning of LLMs. • Knowledge of LLM Ops / ML Ops tools. • Experience with evaluation frameworks for LLMs. • Familiarity with knowledge graphs and semantic search. • Experience building AI copilots, chatbots, or autonomous agents. • Understanding of data privacy, model governance, and responsible AI practices. Education • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field. Preferred Candidate Profile • Strong problem-solving mindset with the ability to design scalable AI systems. • Experience working in fast-paced AI product environments. • Ability to stay updated with rapidly evolving LLM and AI agent ecosystems. • Excellent collaboration and communication skills.