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.