Python Gen Ai Engineer

1 week ago

Hyderabad, Telangana, India Lumin Nxt Inc Full time ₹ 12,00,000 - ₹ 36,00,000 per year

We are seeking a highly skilled Python GenAI Engineer to join our dynamic AI team. You will be responsible for building, deploying, and optimizing Generative AI (GenAI) solutions using large language models (LLMs), MLOps pipelines, and cloud-native services. This role is ideal for someone passionate about cutting-edge AI technologies, especially in the areas of RAG (Retrieval-Augmented Generation), multi-agent frameworks, and AWS AI/ML ecosystem.

Key Responsibilities:

  • Design and implement scalable GenAI applications using Python, LangChain, transformers, LoRA, and other state-of-the-art libraries.
  • Build, fine-tune, and deploy LLMs using AWS SageMaker, Bedrock, and open-source models.
  • Implement Retrieval-Augmented Generation (RAG) pipelines using vector stores, embedding models, and document retrievers.
  • Develop and orchestrate multi-agent systems using frameworks like crewai and Autogen.
  • Integrate automation workflows with tools like n8n to enhance pipeline productivity and AI task orchestration.
  • Build and maintain scalable APIs and microservices using AWS Lambda, Docker, ECS/EKS, and boto3.
  • Monitor, log, and debug models and infrastructure using AWS CloudWatch and Weights & Biases (wandb).
  • Collaborate with cross-functional teams including Data Scientists, ML Engineers, and DevOps to productize and scale GenAI solutions.
  • Ensure best practices in security, performance, and maintainability of AI/ML systems.

Proven experience administering and developing workflows on n8n or similar automation platforms (e.g., Zapier, Make).

- Strong proficiency with APIs, webhooks, and RESTful integrations.

Key Qualifications:

  • 5+ years of Python development experience, with strong coding and software design skills.
  • Hands-on experience with GenAI, LLMs, and libraries like transformers, LangChain, and LoRA.
  • Experience building and fine-tuning models on AWS SageMaker and integrating with AWS Bedrock.
  • Expertise in serverless computing and containerized deployments using AWS Lambda, Docker, ECS/EKS.
  • Familiarity with multi-agent AI frameworks (e.g., crewai, Autogen) and orchestrated automation using n8n workflows.
  • Proficiency in RAG pipeline design with embeddings, vector databases, and hybrid retrieval methods.
  • Strong understanding of boto3, CloudWatch, and general AWS infrastructure.
  • Experience with experiment tracking and visualization using wandb or similar tools.
  • Strong problem-solving skills, communication, and ability to work independently or in a team.
  • Bachelor's or Masters degree in Computer Science, AI/ML, or related field.

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