Senior AI Engineer

Job Purpose
We are seeking a dynamic AI Engineer to join our pioneering Conversational Text AI team. The ideal candidate will possess a strong foundation in model development, UI development and development of APIs, multi-system integrations. You will be involved in end-to-end stage of development life cycle.
Duties and Responsibilities
Deliveries with respect to Conversational Text AI Platform:

• Build and maintain Conversational Text AI system using state-of-the-art LLM frameworks.
• Collaborate with product owners and domain experts to build reusable components for business process.
• Develop core infrastructure and reusable components to support the deployment of conversational AI systems.
• Work on orchestration, prompt engineering, and LLM-powered integrations.
• Implement scalable solutions integrated with respective echo systems and enterprise data platforms.
• Contribute to the design of modular, extensible, enterprise-grade architectures.
• Fine-tune optimization for speed, accuracy, performance and maintainability across business units.
• Contribute to CI/CD automation and maintain operational stability of application services.
  Generative AI Model Optimization:
• Fine-tune LLMs/SLMs with proprietary NBFC data.
• Perform distillation, quantization of LLMs for edge deployment.
• Evaluate and run LLM/SLM models on local/edge server machines.
  Self-Learning Frameworks:
• Build self-learning systems that adapt without full retraining (e.g., learn new rejection patterns from calls).
• Implement lightweight local models to enable real-time learning on the edge.

Key Decisions / Dimensions
Platform Design Delivery, Model Selection, Customization (if any) Testing:

• Choosing the right model for various task and actions.
• Selecting appropriate model so that tasks can complete in efficient manner.
• Defining reusable components in the platform. Delivery using configuration approach should be first preference, in case that does not work should go for customization.
• Defining configuration parameters and incorporate them as platform design.
• Testing and end to end testing of the project deliverable.
• Load balancing between different models.
• Always have switch on/switch off feature.
• Must have all services backed up on primary/HA DR servers.
  Prompt Engineering:
• Prompt Design Development: Crafting prompts that guide AI systems to produce desired outputs for various applications, such as text generation, translation, question answering, and creative writing.
• Testing and Evaluation: Analysing the effectiveness of prompts and refining them based on results to ensure accurate and relevant responses.
• Bias Mitigation: Designing prompts that minimize bias and ensure fair and equitable outcomes from AI systems.

Major Challenges

• Support from other platform owners
• Building a Conversational Text AI BOT that doesn''t just answer but negotiates with human-like reasoning.
• Running large AI models in low-latency, low-bandwidth environments without cloud dependency.
• Getting the end-to-end domain knowledge
• Managing data and information security of the application.

Required Qualifications and Experience
Educational Qualifications

• Educational Background: Bachelors or Masters degree in computer science, Engineering, or a related field.
• Experience: 47 years of experience in AI/ML, with exposure to Python, Node.JS, JavaScript, HTML/CSS, Redis, Postgres, Azure COSMOS, DevOps, CI/CD.
• Strong programming skills in languages such as Python, Node.JS, JavaScript, HTML/CSS.
• Familiarity with Redis, Postgres, Vector Embeddings, Speech-to-Text Text-to-Speech Services, Azure COSMOS, DevOps, CI/CD, Lang-Chain or Lang-Graph.
• Experience building with or integrating LLMs for task automation, reasoning, or autonomous workflows
• Strong understanding of prompt engineering, tool calling, and agent orchestration.