AI Systems Developer

1 day ago

Coimbatore, Tamil Nadu, India beBeeSoftware Full time ₹ 25,00,000 - ₹ 35,00,000

Key Roles and Responsibilities:

  • Design, develop, and integrate large language model (LLM) applications with Python-based frameworks.
  • Architect scalable pipelines including prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and evaluation for AI innovation.
  • Create efficient microservices and REST APIs for Artificial Intelligence features to enhance business performance.
  • Collaborate with Machine Learning Operations teams to deploy and monitor AI models in production ensuring seamless integration.
  • Ensure performance optimization, cost efficiency, and security in LLM workflows while maintaining high-quality standards.
  • Guide the team on Python best practices, code reviews, and technical problem-solving to foster a culture of excellence.
  • Stay updated on emerging AI/LLM advancements and propose strategic adoption where beneficial.

Mandatory Skills and Qualifications:

  • Strong proficiency in Python programming languages including FastAPI and Flask.
  • Solid experience with Large Language Model integration including OpenAI API, Hugging Face Transformers, LangChain, and LlamaIndex.
  • Understanding of RAG pipelines including vector databases like Pinecone, Weaviate, FAISS, and Milvus.
  • Experience with prompt engineering & evaluation techniques, knowledge of MLOps tools including MLflow, Kubeflow, and Langfuse, and deployment on AWS/GCP/Azure.
  • Familiarity with containerization and orchestration using Docker and Kubernetes.
  • Strong grasp of REST APIs, GraphQL, and microservices architecture, knowledge of model fine-tuning and performance optimization.

Preferred Skills and Qualifications:

  • Excellent leadership and mentoring abilities, strong problem-solving and analytical skills.
  • Effective communication with technical and non-technical stakeholders.
  • Ability to work in a fast-paced, evolving AI environment.
  • Experience with agentic AI or Model Context Protocol (MCP), background in data pipelines including ETL and streaming data.
  • Exposure to AI security & compliance practices, prior work in scalable enterprise AI products.

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