Tech Stack
AirflowApacheAWSAzureCloudNeo4jPostgresPySparkPythonRedis
About the role
- 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.
Requirements
- A minimum of 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.
- flexible work environment
- empowering individual growth
- well-being and belonging
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
PythonAI frameworksfine-tuning large language modelsRetrieval-Augmented Generationvector databasesprompt engineeringCI/CD processes