Senior Generative AI Engineer - RAG/LLM

What are we looking for?

We're in search of a Senior Generative AI Engineer who brings deep expertise in building and deploying large language models and AI systems at scale. This role is for those with extensive experience in developing production-grade AI solutions, particularly in the realm of generative AI and language models. The ideal candidate will play a crucial role in advancing our AI capabilities, designing intelligent agent architectures, and implementing sophisticated RAG pipelines that power our products used by thousands of data teams worldwide.

Professional Experience:

- 7 - 10 years of hands-on ML/AI experience with at least 2 year of hands-on experience in GenAI/LLM projects

- Track record of successfully deploying ML/AI systems in production environments

- Experience working with enterprise customers and understanding their unique requirements

Technical Skills Required:

- Strong programming skills in Python, including expertise in ML stack (Hugging Face, NumPy, Pandas, scikit-learn)

- Production experience with deep learning frameworks (PyTorch/Tensorflow) and transformer architectures

- API development expertise (FastAPI) and production deployment experience

- Proven experience with prompt engineering best practices and LLM evaluation metrics

Technical Skills Preferred:

Infrastructure & Deployment

- Experience with vector databases (e.g., Pinecone, Weaviate) and RAG pipelines

- Experience with observability and monitoring of LLM applications

- Proficiency in model compression, distillation, and deployment at scale

Model Development & LLMs

- Expertise in semantic search and embedding models

- Experience in LLM frameworks (LangChain, LlamaIndex) and agentic AI systems

- Advanced model fine-tuning techniques, including LoRA, Prompt Tuning, and Adapter Training

Why should you join ?

Projects You'll Work On :

- Advanced AI Agent Architecture: Design and implement sophisticated multi-agent systems that can understand context, make decisions, and enable seamless collaboration between AI and human data professionals.

- Large-Scale RAG Systems: Build and optimize retrieval-augmented generation pipelines that can efficiently process and utilize enterprise-scale knowledge bases.

- Model Optimization & Deployment: Implement advanced techniques (LoRA, Prompt Tuning) to adapt off-the-shelf models for specific enterprise data tasks, ensuring faster, more accurate performance.

- Scalable AI Infrastructure: Develop and optimize cloud-native architectures (AWS, Kubernetes) for large-scale training, inference, and multi-agent orchestration.

- Enterprise Security & Compliance: Implement robust security measures for LLM applications, including data anonymization, prompt injection prevention, and compliance with enterprise security standards.

Impact :

- Innovation Leadership: Shape the future of enterprise AI by developing novel approaches to autonomous data operations and AI-driven automation.

- Product Development: Direct influence on our flagship products, DataPilot and DataMates, working on cutting-edge features that define the next generation of AI-powered data tools.

- Team Growth: Help build and mentor a growing team of AI engineers, shaping our technical culture and practices.

- Open Source Contribution: Lead and contribute to our open-source initiatives, establishing yourself as a thought leader in the AI community.

- Technical Growth: Opportunity to work with the latest advancements in AI technology and shape the architecture of next-generation AI systems.