Generative AI / Machine Learning Engineer – LLM, RAG & AI Agents
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Summary
Senior engineer building end-to-end generative AI solutions — chatbots, voicebots, AI agents and Talk-to-Data systems — covering data processing, RAG pipelines, LLM integration and deployment, plus solution architecture and pre-sales support. Core stack: Python, PyTorch, Hugging Face, LangChain/LangGraph, Azure/GCP, OpenAI/Gemini APIs and vector databases.
Project Description
We are looking for a Senior Generative AI Engineer to join a project focused on developing advanced AI solutions, including chatbots, voicebots, AI agents and Talk-to-Data systems.
You will be responsible for designing and implementing end-to-end Generative AI solutions, from data processing and RAG pipelines to LLM integration and deployment. The role also involves working closely with business stakeholders, contributing to solution architecture and supporting pre-sales activities.
Requirements
- Strong experience in Machine Learning and Generative AI, particularly LLMs, NLP or multimodal models.
- Good understanding of Deep Learning concepts.
- Strong Python programming skills and knowledge of object-oriented programming.
- Working knowledge of SQL and vector databases.
- Hands-on experience with Azure or GCP.
- Practical knowledge of PyTorch, NumPy, Hugging Face, LangChain and LangGraph.
- Experience integrating OpenAI or Gemini APIs.
- Proven experience designing and implementing RAG solutions.
- Hands-on experience with MCP servers and clients for LLM-based agents.
- Experience with microservice architectures and AI application deployment.
- Ability to translate business needs into technical solutions.
- Strong analytical, problem-solving and communication skills.
Nice to Have
- Experience with Databricks.
- Commercial experience delivering Generative AI, NLP or Computer Vision projects.
- Experience with multimodal AI and production-grade AI agents.
- Experience in technical consulting or pre-sales.
- Ability to mentor and guide junior engineers.