Lead - AI Unit/Senior Lead - AI Unit

Bajaj Finance · Pune

  • Experience6–8 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Posted1 Oct 2026

About Bajaj Finance

Bajaj Finance is hiring in Pune in financial services. This role looks for around 6+ years of experience.

Skills

  • Prompt engineering
  • Agent orchestration
  • Apex Programming
  • Lightning Web Components
  • Aura Components
  • Visualforce
  • Salesforce Flows
  • Microsoft Foundry
  • Microsoft Copilot Studio
  • Agentforce
  • LangChain
  • Semantic Kernel
  • CrewAI
  • LangGraph
  • Agent Development Kit
  • MCP
  • A2A
  • LLM fine-tuning
  • LLM distillation
  • LLM quantization
  • API development
  • UI development
  • CI/CD

The role

A generative AI engineer at a financial services company builds autonomous software agents for business process automation, using Agent orchestration, Prompt engineering and Salesforce. The role also develops reusable enterprise components and optimizes LLMs for edge deployment.

Full job description

Job Purpose

We are seeking a dynamic AI Engineer to join our pioneering Agentic AI team. The ideal candidate will possess a strong foundation in delivering projects on both SaaS & PaaS based platforms, Prompt Engineering, UI development and development of APIs. You will be involved in end-to-end stage of development life cycle.

Duties and Responsibilities

Deliveries with respect to Agentic AI Platform: 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 architecture. 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: Writing and Optimizing Prompts 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 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.

Required Qualifications and Experience

Qualifications a) Bachelor??s or Master??s degree in Computer Science, Engineering, or a related field. b) Experience: 6??8 years of experience in Apex Programming, Lightning Web Components (LWC), Aura Components, Visual Force, Salesforce Flows etc. c) Experience in managing team of 5-8 team members

d) Work Experience

Strong understanding of prompt engineering, tool calling, and agent orchestration.

Good understanding of Microsoft Foundry + MS CoPilot Studio/ Agentforce or Equivalent.

Strong programming skills in languages such as Apex Programming, Lightning Web Components (LWC) &

Visual Force.

Familiarity with LangChain, Semantic Kernel, CrewAI, or LangGraph.

Understanding of Agentforce, Apex, Salesforce Flows.

Familiarity with the Agent Development Kit (ADK) and protocols like MCP & A2A

Experience of Managing a team