Job Summary :

- 10 years of strong technical background, including a deep understanding of AI concepts and methodologies.

- 3- 5 years hands on experience with LLM (commercial and open source), LangChain, LlamaIndex, agentic AI, Retrieval Augmented Generation, and Vector Databases

- 3-5 years of experience with graph databases (Neo4J and Cypher would be a big plus

- Txt2sql hand on experience is a plus

- Programing languages such as Python and Java and familiarity with libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, Scipy, Pandas, etc

- Solid understanding of experimental design, hypothesis testing, and casual inference methods

- Experience working with agile methodologies and tools.

- A passion for innovation and a desire to push the boundaries of AI.

- Financial industry experience would be a plus.

Key Responsibilities :

- Leverage 10+ years of technical expertise to design and implement AI solutions, including a comprehensive understanding of AI concepts and methodologies.

- Utilize 3- 5 years of hands-on experience with LLMs (both commercial and open-source), LangChain, LlamaIndex, agentic AI, Retrieval-Augmented Generation (RAG), and vector databases to develop and deploy advanced AI applications.

- Apply 3-5 years of experience with graph databases, particularly Neo4j and Cypher, to model and query complex data structures effectively.

Required Skills and Experience :

- Demonstrate proficiency in programming languages such as Python and Java, and utilize libraries/frameworks like TensorFlow, PyTorch, scikit-learn, SciPy, and Pandas for data analysis and machine learning tasks.

- Apply solid understanding of experimental design, hypothesis testing, and causal inference methods to validate AI models and algorithms.

- Collaborate within agile teams, utilizing agile methodologies and tools to deliver AI solutions efficiently.

- Foster a passion for innovation, continuously exploring new AI techniques and methodologies to push the boundaries of AI capabilities.

- Experience in the financial industry is advantageous, providing context for applying AI solutions in financial applications.

Preferred Qualifications :

- Extensive experience in AI/ML, with a focus on LLMs, graph databases, and vector-based retrieval systems.

- Proficiency in programming languages and AI/ML frameworks.

- Strong analytical skills, with expertise in statistical analysis and experimental design.

- Experience working in agile environments, with a collaborative approach to problem-solving.

- Interest in the financial industry and its applications of AI technologies.

Education : BE/Btech/BCA/MCA or similar qualification