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Senior AI Engineer - AI Unit, Agentic AI, Agentic AI

0 - 7 years

0 Lacs

pune maharashtra

Posted:2 months ago| Platform: Indeed logo

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Skills Required

ai model development ui software support deployment orchestration engineering crm data design automation stability distillation quantization server learning customization configuration testing translation writing evaluation effectiveness latency security ml python node.js javascript react gcp programming reasoning power kit communication

Work Mode

On-site

Job Description

    AI UnitPune Corporate Office - Mantri
    Posted On
    20 Aug 2025
    End Date
    20 Aug 2026
    Required Experience
    4 - 7 Years

BASIC SECTION

Job Level

GB04

Job Title

Senior AI Engineer - AI Unit, Agentic AI, Agentic AI

Job Location

Country

India

State

MAHARASHTRA

Region

West

City

Pune

Location Name

Pune Corporate Office - Mantri

Tier

Tier 1

Skills

SKILL

SKILLS AS PER JD

Minimum Qualification

OTHERS

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 model development, 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 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

    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

    Educational Qualifications
  • 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.

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