AI Engineer

We are looking for a highly skilled

AI Agent Engineer

having 3-5 years of experience, to design and build intelligent, production-grade AI systems that power marketing automation, campaign optimization, and customer engagement. This role combines deep expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI agent frameworks with practical experience integrating solutions into real-world marketing ecosystems. The ideal candidate will be hands-on, innovation-driven, and capable of deploying scalable, secure AI solutions that deliver measurable business outcomes.

Key Responsibilities

Design and develop intelligent AI agents for marketing automation and campaign optimization Build social listening agents to track brand mentions, sentiment analysis, and competitor activity across digital channels Develop AI-driven lead scoring and prospecting systems integrated with CRM platforms Implement Retrieval-Augmented Generation (RAG) architectures for knowledge-based marketing assistants Integrate AI agents with marketing platforms such as HubSpot and other third-party tools Optimize prompts, workflows, context management, memory handling, and performance Deploy AI agents securely on cloud infrastructure with scalability and reliability in mind Monitor, evaluate, and continuously improve model accuracy, performance, and ROI Maintain technical documentation, architecture diagrams, and best practices

Technical Requirements

Must-Have Skills

Strong Python programming skills Hands-on experience with LLM APIs (OpenAI, Azure OpenAI, Anthropic, vLLM, or open-source LLMs) Experience with AI agent frameworks (LangChain, CrewAI, AutoGen, or similar) Solid prompt engineering expertise and prompt optimization techniques Experience building and consuming RESTful APIs Hands-on experience with vector databases (Pinecone, Qdrant, PGVector, etc.) Strong understanding of RAG architecture and implementation patterns Familiarity with Git and version control best practices