Large Language Model Architect

 About The Role  



Project Role :Large Language Model Architect




Project Role Description :Architect large language models (LLM) that can process and generate natural language. Design neural network parameters, trained on large quantities of unlabeled text data.


Must have skills :Large Language Models



Good to have skills :NA
Minimum

3 year(s) of experience is required



Educational Qualification :15 years full time education

SUMMARY:We are looking for a technical enthusiast with strong expertise in Python and a solid understanding of AI/ML concepts to contribute to the development of Data Agents powered by Agentic AI. The ideal AI enthusiast will play a key role in designing, implementing, and optimizing intelligent agents that can autonomously process data, interact with systems, and support business decision-making. ROLES AND RESPONSIBILITIES:

Design & Development:Build and deploy intelligent Data Agents using Agentic AI frameworks and Python-based development to enable autonomous decision-making.

Data Engineering:Implement scalable and efficient data pipelines leveraging Python/Py Spark to support AI-driven workflows and analytics.

AI/ML Integration:Apply advanced AI/ML concepts within Data Agents to enable automation, reasoning, and intelligent decision support.

Prompt Engineering:Develop and optimize prompts to improve performance of large language models (LLMs) and enhance agentic workflows.

Cross-functional Collaboration:Partner with product, data science, and engineering teams to identify business use cases and deliver AI-powered solutions.

Innovation & Enhancement:Continuously refine agent capabilities to improve adaptability, efficiency, and accuracy in dynamic business environments. TECHNICAL EXPERIENCE:

Min 2.5 years of professional experience in the required skills - having min 1 year of Gen AI experience

Proficiency in Python, Knowledge Graphs, and experience with Py Spark for data handling.

Foundational understanding of AI/ML concepts (e.g., supervised/unsupervised learning, NLP, LLMs).

Growth mindset and agility to adapt in a rapidly evolving AI landscape.

Experience with ETL/ELT pipelines.

Proficiency in different types of database modeling (relational, NoSQL, graph, etc.).

Experience building APIs (e.g., Fast API) and Server-Sent Events (SSE).

Knowledge of search technologies, including Elasticsearch, vectorization, and embeddings.

Experience developing modern frontends using Angular or React frameworks.

Design and build Data Agents leveraging Agentic AI frameworks and Python-based development.

Implement scalable data pipelines using Python/Py Spark to support AI-driven workflows.

Integrate AI/ML concepts into Data Agents for automation, reasoning, and decision support.

Apply prompt engineering techniques to optimize performance of LLMs and agentic workflows.

Collaborate with product, data science, and engineering teams to identify use cases and deliver AI-enabled solutions.

Continuously enhance agent capabilities to improve adaptability, accuracy, and efficiency.

Stay ahead of emerging technologies in Agentic AI, ML, and autonomous systems to drive innovation.

Strong problem-solving mindset, with the ability to build and adapt intelligent systems.

Excellent communication skills to articulate technical ideas to cross-functional teams. ADDITIONAL ATTRIBUTES:

Familiarity with LLMs and frameworks for building agentic workflows.

Hands-on experience with ML frameworks such as scikit-learn, TensorFlow, or Py Torch.

Understanding of cloud-based AI services (AWS SageMaker, Azure ML, GCP Vertex AI). EDUCATION QUALIFICATIONS:

A 15-year full-time education is required

 Qualification 15 years full time education