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Lead - AI Engineer

Ciena India Private Limited

On-site Full-time Lead Today

About the role

About

As the global leader in high-speed connectivity, Ciena is committed to a people‑first approach. Our teams enjoy a culture focused on prioritizing a flexible work environment that empowers individual growth, well‑being, and belonging. We’re a technology company that leads with our humanity—driving our business priorities alongside meaningful social, community, and societal impact.

Blue Planet, a division of Ciena, is seeking a dynamic AI Engineer to drive advancements in AI technologies and frameworks, contributing to cutting‑edge developments across diverse domains.

How You Will Contribute

  • Design and develop AI agents using frameworks like LangChain, LangGraph, Langflow, and MCP Servers.
  • Fine‑tune and optimize large language models (LLMs) such as GPT models, Llama, and others for diverse applications.
  • Implement Retrieval‑Augmented Generation (RAG) techniques and integrate vector databases like Qdrant and ChromaDB.
  • Enhance AI agent operations with tools like langfuse and litellm, ensuring robust security and guardrails.
  • Leverage cloud platforms such as AWS, Google Cloud, and Azure for scalable AI solution deployment.
  • Build and manage databases using Postgres, Neo4j, and Clickhouse for efficient data handling.
  • Utilize technologies like Apache Airflow, Redis, Mlflow, Minio, Apache Kedro, and PySpark for workflow optimization and data processing.

Must Haves

  • 6+ years of experience in AI engineering with proficiency in Python.
  • Expertise in AI frameworks such as LangChain and LangGraph, or similar agentic AI frameworks.
  • Proven experience in fine‑tuning large language models (LLMs) and implementing Retrieval‑Augmented Generation (RAG) techniques.
  • Strong knowledge of vector databases and AI agent security protocols.
  • Familiarity with cloud platforms and database technologies.
  • Experience with prompt engineering techniques and CI/CD processes.
  • Background in leveraging tools like Apache Airflow, Redis, Mlflow, Minio, and Apache Kedro.

Nice to Haves

  • Experience with PySpark for large‑scale data processing.
  • Knowledge of emerging AI frameworks and technologies.
  • Advanced understanding of AI agent optimization and collaborative systems.
  • Exposure to cloud‑native tools and services for AI deployment.
  • Familiarity with advanced database architectures and tools.
  • Interest in contributing to open‑source AI initiatives.
  • Passion for driving innovation in AI technologies.

Equal Opportunity Statement

At Ciena, we are committed to building and fostering an environment in which our employees feel respected, valued, and heard. Ciena values the diversity of its workforce and respects its employees as individuals. We do not tolerate any form of discrimination. Ciena is an Equal Opportunity Employer, including disability and protected veteran status. If contacted in relation to a job opportunity, please advise Ciena of any accommodation measures you may require.

Discover how Ciena's unique blend of deep humanity and relentless innovation creates an exceptional workplace culture. Explore CienaLife.

#LI-FA

Requirements

  • 6+ years of experience in AI engineering with proficiency in Python.
  • Expertise in AI frameworks such as LangChain and LangGraph, or similar agentic AI frameworks.
  • Proven experience in fine-tuning large language models (LLMs) and implementing Retrieval-Augmented Generation (RAG) techniques.
  • Strong knowledge of vector databases and AI agent security protocols.
  • Familiarity with cloud platforms and database technologies.
  • Experience with prompt engineering techniques and CI/CD processes.
  • Background in leveraging tools like Apache Airflow, Redis, Mlflow, Minio, and Apache Kedro.

Responsibilities

  • Design and develop AI agents using frameworks like LangChain, LangGraph, LangFlow, and MCP Servers.
  • Fine-tune and optimize large language models (LLMs) such as GPT models, Llama, and others for diverse applications.
  • Implement Retrieval-Augmented Generation (RAG) techniques and integrate vector databases like Qdrant and ChromaDB.
  • Enhance AI agent operations with tools like langfuse and litellm, ensuring robust security and guardrails.
  • Leverage cloud platforms such as AWS, Google Cloud, and Azure for scalable AI solution deployment.
  • Build and manage databases using Postgres, Neo4j, and Clickhouse for efficient data handling.
  • Utilize technologies like Apache Airflow, Redis, Mlflow, Minio, Apache Kedro, and PySpark for workflow optimization and data processing.

Skills

Apache AirflowApache KedroAWSAzureChromaDBClickhouseCI/CDGPTGoogle CloudLangChainLangGraphLangFlowLiteLLMLLMsLlamaMlflowMCP ServersMinioNeo4jPostgresPrompt EngineeringPySparkQdrantRAGRedis

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