Senior Artificial Intelligence Engineer - LLM

Role Overview :

We are seeking a Senior AI Engineer with deep expertise in Generative AI, RAG (Retrieval-Augmented Generation), and Large Language Models (LLMs) to drive the development of advanced AI capabilities within our platform. In this role, you will work on cutting-edge applications leveraging financial datasets and LLMs to deliver intelligent, scalable, and user-centric AI solutions.

Key Responsibilities :

- Vector Search & Retrieval : Leverage vector databases such as FAISS, Pinecone, Weaviate, or Qdrant for semantic search, document ranking, and high-speed querying.

- LLM Fine-Tuning & Integration : Customize open-source and commercial models (e.g., OpenAI, LLaMA, Mistral, Claude) for context-aware, domain-adapted use cases.

- Prompt Engineering : Develop optimized prompts, context compression techniques, and chunking strategies to improve model reasoning and response quality.

- Platform Integration : Collaborate with product, backend, and frontend teams to seamlessly integrate AI-driven features into user-facing applications.

- Performance Optimization : Ensure scalable inference, latency reduction, and model performance tuning using tools like quantization, pruning, or distillation.

- Research & Innovation : Stay on the bleeding edge of GenAI, NLP, and autonomous agent systems. Prototype new ideas and experiment with innovative architectures.

Required Skills & Experience :

- Experience working with vector databases (e.g., FAISS, Pinecone, Weaviate, Qdrant).

- Proficient in Python, with solid knowledge of libraries such as Transformers, HuggingFace, OpenAI API, LangChain, etc.

- Familiarity with document embeddings, retrieval techniques, and efficient chunking strategies.

- Experience deploying AI/ML models on cloud platforms (AWS, GCP, or Azure).

- Ability to independently handle projects in fast-paced, agile environments especially in a startup or scale-up setting.

Good to Have :

- Understanding of LLMOps, observability in GenAI pipelines, and maintaining AI in production.

- Familiarity with containerization (Docker), Kubernetes, and API development.

Senior AI Engineer