Large Language Model (LLM) Executive

Job Description

Company Profile

A forward-thinking IT products and services company committed to delivering innovative technology solutions that drive operational efficiency and business progress for its clients. The organization is actively building capabilities in Artificial Intelligence, Large Language Models, and intelligent automation — positioning itself at the leading edge of enterprise AI adoption across customer experience, sales, marketing, and finance functions.

Position Overview

The AI & LLM Executive will play a hands-on supporting role in the development, deployment, and maintenance of AI-driven solutions within the organization. Working closely with internal technology and business teams, the incumbent will assist in building LLM-based workflows, RAG pipelines, autonomous agents, and intelligent chatbots — contributing directly to the organization’s enterprise AI roadmap. This is an excellent entry-level opportunity for a technically curious individual looking to build a strong foundation in applied AI, prompt engineering, and open-source LLM integration within a professional IT environment.

Qualifications

• Bachelor’s degree or diploma in Computer Applications, Computer Science, or Information Technology — BCA, MCA, B.Sc. (CS / IT), or Diploma in IT / Computer Engineering
• Basic working knowledge of Python or any scripting / programming language
• Familiarity with AI tools, ChatGPT-like platforms, and conversational AI interfaces
• Awareness of open-source LLM frameworks such as LLaMA, Mistral, or equivalent models is an advantage
• Strong written communication skills for documentation, SOP preparation, and reporting

Key Responsibilities

1. AI Solution Development Support

• Support the development and deployment of AI-driven solutions across business functions including Customer Experience (CX), Sales, Marketing, and Finance
• Assist senior team members in translating business requirements into AI use cases and solution blueprints
• Contribute to the evaluation of AI outputs and help refine solutions based on performance feedback

2. LLM Integration & Workflow Building

• Assist in integrating open-source AI and LLM frameworks with enterprise systems, tools, and platforms
• Support the building and testing of LLM-based workflows, Retrieval-Augmented Generation (RAG) pipelines, autonomous agents, and intelligent chatbots
• Participate in the setup, configuration, and iterative improvement of AI-powered automation tools

3. Data Preparation & Prompt Engineering

• Assist with data collection, cleaning, and preparation tasks required for AI model training, fine-tuning, and evaluation
• Create, test, and optimize prompts for LLM-based applications to improve accuracy, relevance, and output quality
• Perform dataset annotation and labelling tasks as required for supervised learning and evaluation workflows

4. Collaboration & Deployment Support

• Collaborate with internal cross-functional teams — technology, product, and business units — to deploy and maintain AI-driven solutions in production environments
• Support UAT (User Acceptance Testing) activities for AI tools before organizational rollout
• Troubleshoot basic issues in AI workflows and escalate complex technical problems with structured observations

5. Documentation & Reporting

• Prepare clear and accurate documentation for AI workflows, integration processes, and system configurations
• Draft Standard Operating Procedures (SOPs) for AI tools and LLM-based applications used internally
• Compile and share regular progress reports on assigned tasks and solution development milestones

Skills Required

• AI Tools Familiarity: Working knowledge of AI platforms and ChatGPT-like conversational tools; ability to use and evaluate AI-generated outputs effectively
• Open-Source LLM Awareness: Basic understanding of open-source Large Language Models (LLaMA, Mistral, Falcon, or similar) and their application in enterprise use cases
• Python / Coding Knowledge: Basic proficiency in Python or equivalent coding skills sufficient for scripting, data handling, and API interaction
• Prompt Engineering: Ability to craft, test, and iteratively refine prompts for LLM-based applications to achieve desired outputs
• RAG & Agent Frameworks: Awareness of or willingness to learn Retrieval-Augmented Generation (RAG) pipelines and autonomous agent frameworks (LangChain, LlamaIndex, or equivalent)
• Data Handling: Basic capability in data preparation, annotation, and structured dataset management for AI workflows
• Documentation & SOP Writing: Strong written communication and documentation skills to produce clear, structured SOPs and technical reports
• Collaborative Mindset: Ability to work effectively within cross-functional teams, take direction, and contribute proactively to team deliverables

Special Requirements

• Candidates must demonstrate genuine interest in Artificial Intelligence, Large Language Models, and enterprise AI applications a portfolio, personal project, or course certification in AI / ML will be a strong advantage
• Hands-on experience or academic exposure to LLM integration, RAG pipelines, or chatbot development will be preferred over purely theoretical knowledge
• Willingness to learn new AI frameworks, platforms, and enterprise integration tools as the role evolves is essential