Generative AI Engineer

Location: Remote

Experience: 2+ to 7 Years

We are looking for a Generative AI Engineer to join our growing team. The ideal candidate should have

hands-on experience working with LLMs, RAG pipelines, NLP, and AI model deployment. This role offers a

great opportunity to work on cutting-edge AI solutions and build real-world applications under the

guidance of a senior team.

Responsibilities:

• Collaborate with product and engineering teams to understand AI use cases and deliver solutions using Generative AI and LLMs (GPT, Claude, LLaMA, Mistral).
• Deploy and monitor models using cloud services such as AWS or Azure.
• Work with DevOps and backend teams to ensure smooth integration and performance tuning.
• Design, build, and fine-tune AI models for use in NLP tasks, chatbots, and content generation systems.
• Develop and optimize Retrieval-Augmented Generation (RAG) pipelines for scalable performance.
• Stay current with the latest trends in AI research, LLM development, and open-source AI tooling.
• Support data preprocessing, prompt engineering, and experimentation with large language models.

Required skillset:

• 2 to 4 years of experience in AI/ML development or research.
• Strong proficiency in Python and libraries such as Transformers, LangChain, Hugging Face, etc.
• Good understanding of LLMs, their capabilities, limitations, and use in production.
• Exposure to cloud services (AWS, Azure, or GCP) for deploying and managing AI workloads.
• Solid understanding of NLP concepts like embeddings, tokenization, summarization, etc.
• Familiarity with API integration and model deployment using tools like Docker/FastAPI.
• Analytical mindset, with good communication and problem-solving skills.
• Ability to work in an agile, fast-paced team environment.

Good to have:

• Experience building or deploying RAG pipelines and using vector databases (e.g., FAISS, Pinecone, Weaviate).
• Knowledge of MLOps, model monitoring, and lifecycle management.
• Exposure to CI/CD workflows and version control tools (e.g., Git, GitHub Actions).
• Previous contributions to open-source AI projects or participation in AI hackathons.
• Awareness of AI ethics, privacy, and responsible AI practices.