Technical Development Lead

About the Company

Empowered By InnovationBirlasoft, a global leader at the forefront of Cloud, AI, and Digital technologies, seamlessly blends domain expertise with enterprise solutions. The company’s consultative and design-thinking approach empowers societies worldwide, enhancing the efficiency and productivity of businesses. As part of the multibillion-dollar diversified CKA Birla Group, Birlasoft with its 12,000+ professionals, is committed to continuing the Group’s 170-year heritage of building sustainable communities.

About the Role

This is not a data science role. This is completely implementation centric role in core AgenticAI application engineering projects. The Implementation Technical Developer will be responsible for designing, developing, and deploying cutting-edge Agentic AI solutions using the latest Large Language Models (LLMs) and frameworks. This role requires deep expertise in Python programming, cloud platforms (Azure), and advanced AI techniques such as Agent Patterns, Agent to Agent, MCP, fine-tuning, LLMOps, and Responsible AI. will lead to the development of scalable, secure, and efficient Agentic AI applications, ensuring alignment with business goals and technical requirements.

Responsibilities

• Design and Develop:

  Create scalable and modular solutions for AgenticAI applications using frameworks like Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain.

• Python Development:

  Core hands on experience development of Python-based AgenticAI applications, ensuring high-quality, maintainable, and efficient code.

• Data Curation Automation:

  Build tools and pipelines for automated data curation, preprocessing, and augmentation to support LLM training and fine-tuning.

• Cloud Integration:

  Design and implement solutions leveraging Azure LLM ecosystems, ensuring seamless integration with existing cloud infrastructure.

• Fine-Tuning Expertise:

  Apply advanced fine-tuning techniques such as PEFT, QLoRA, and LoRA to optimize LLM performance for specific use cases.

• LLMOps Implementation:

  Establish and manage LLMOps pipelines for continuous integration, deployment, and monitoring of LLM-based applications.

Qualifications

Relevant Experience: 7-10 Years

Required Skills

• Python Programming:

  Deep expertise in Python for building AgenticAI applications and automation tools.

• LLM Frameworks:

  Proficiency in frameworks like Autogen/Crew.ai/LangGraph, LlamaIndex, and LangChain.

• Large-Scale Data Handling & Solution:

  Design and implement solution for handling large-scale structured and unstructured data.