Lead Engineer GenAI

5 years

12 - 15 Lacs

Posted:17 hours ago| Platform: GlassDoor logo

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Work Mode

On-site

Job Type

Full Time

Job Description

About Kadel Labs:

Kadel Labs is a leading IT services company delivering top-quality technology solutions since 2017, focused on enhancing business operations and productivity through tailored, scalable, and future-ready solutions. With deep domain expertise and a commitment to innovation, we help businesses stay ahead of technological trends. As a CMMI Level 3 and ISO 27001:2022 certified company, we ensure best-in-class process maturity and information security, enabling organizations to achieve their digital transformation goals with confidence and efficiency.

Job Title: Lead Engineer

Location: Bhopal Experience Required: 5+ years

Job Summary

We are seeking a highly skilled Lead Engineer to design and deliver Agentic AI solutions leveraging frameworks such as Autogen, LangGraph, LangChain, and Retrieval-Augmented Generation (RAG).
In this role, you will lead technical initiatives to build scalable, intelligent systems that combine LLMs, custom ML models, and data-driven reasoning.You will collaborate closely with clients and internal teams to architect innovative solutions that solve real-world challenges using cutting-edge AI technologies.

Key Responsibilities

  • Architect and develop Agentic AI solutions using Autogen, LangGraph, LangChain, and RAG.
  • Design multi-agent orchestration flows, enabling reasoning, coordination, and tool-use among AI agents.
  • Build and deploy custom ML models for regression, classification, and NLP tasks.
  • Lead and mentor a team of engineers, providing technical guidance and fostering innovation.
  • Collaborate with clients and internal engineering teams to define AI solution strategies, translate business requirements into technical architectures, and drive successful project delivery.
  • Fine-tune and optimize LLMs using LoRA, QLoRA, and other advanced optimization techniques.
  • Develop and maintain data pipelines ensuring scalability, quality, and data integrity.
  • Implement CI/CD and MLOps pipelines for automated testing, deployment, and monitoring.
  • Stay current with emerging trends in Agentic AI, LLMOps, and applied machine learning research.

Required Qualifications

  • B.Tech / M.Tech / MCA in Computer Science, AI, or a related field.
  • 5+ years of experience in AI/ML engineering, with hands-on work in Agentic AI systems.
  • Proven expertise with Autogen, LangGraph, LangChain, and RAG frameworks.
  • Strong proficiency in Python and frameworks such as PyTorch, TensorFlow, or Hugging Face Transformers.
  • Experience in LLM fine-tuning and model optimization (LoRA, QLoRA, TensorRT, mixed precision, Apex).
  • Deep understanding of vector databases (Faiss, Qdrant, Annoy) and retrieval frameworks.
  • Strong background in data engineering, MLOps, and model deployment workflows.
  • Excellent communication, collaboration, and client-facing skills with the ability to translate complex AI concepts into practical business solutions.

Nice to Have

  • Experience with multi-agent frameworks (CrewAI, SmolAgents, OpenDevin).
  • Knowledge of NLP, computer vision, or multimodal AI systems.
  • Understanding of AI ethics, safety, and bias mitigation practices.
  • Familiarity with MLOps tools like MLflow, DVC, or Weights & Biases.
  • Experience working in agile service delivery environments or with cross-functional client teams.

Benefits

Why Join Kadel Labs?

  • Opportunity to work with a fast-growing, innovative company.
  • A dynamic work environment where creativity and new ideas are encouraged.
  • Competitive salary and benefits package.
  • Professional development opportunities in a people-first culture.

Visit us:https://kadellabs.com/

https://in.linkedin.com/company/kadel-labs

https://www.glassdoor.co.in/Overview/Working-at-Kadel-Labs-EI_IE4991279.11,21.html

Job Types: Full-time, Permanent

Pay: ₹1,200,000.00 - ₹1,500,000.00 per year

Benefits:

  • Health insurance
  • Provident Fund

Work Location: In person

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