Senior AI Engineer

Location Name:

Job Purpose

Duties And Responsibilities

•  Build and maintain autonomous software agents using state-of-the-art LLM frameworks.
•  Collaborate with product owners and domain experts to build reusable components for business process automation.
•  Develop core infrastructure and reusable components to support the deployment of agent-based AI systems.
•  Work on agent orchestration, prompt engineering, and LLM-powered integrations.
•  Implement scalable solutions integrated with CRM systems and enterprise data platforms.
•  Contribute to the design of modular, extensible, enterprise-grade architectures.
•  Fine-tune and evaluate AI agents for speed, accuracy, performance and maintainability across business units.
•  Contribute to CI/CD automation and maintain operational stability of agent 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

•  Choosing the right model for various agentic and autonomous actions.
•  Selecting appropriate model so that Agents can complete the autonomous tasks 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
•  Agents must learn from failed interactions
•  Building a Agents 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 agentic application.
  

Educational Qualifications

Required Qualifications and Experience

•  Educational Background: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
•  Experience: 4–7 years of experience in AI/ML, with exposure to Python, Node.JS, JavaScript, React, Java.
• Good understanding of Google GCP/Microsoft Foundry + MS CoPilot Studio/ Agentforce or Equivalent.
• Strong programming skills in languages such as Python, Node.JS, JavaScript, React, Java.
• Familiarity with LangChain, Semantic Kernel, CrewAI, or LangGraph.
• Experience building with or integrating LLMs for task automation, reasoning, or autonomous workflows
• Understanding of Microsoft Copilot Studio, BigQuery, Power Apps, and Power BI
• Familiarity with the Agent Development Kit (ADK) and MCP (Multi-agent Communication Protocol)
• Strong understanding of prompt engineering, tool calling, and agent orchestration.