Key Skills: Python, Generative AI, LangChain Development, Apache Spark, Retrieval-Augmented Generation, Lang graph, Fast Api, BGE Embedding Models, LLM, Hugging face, Prompt Engineering, Vector Database Integration, Open AI
Roles and Responsibilities:
- Design and develop AI/ML applications using Python, Generative AI, LangChain, LangGraph, FastAPI, and RAG patterns.
- Build scalable data pipelines and processing workflows using Apache Spark, Hadoop, and Kafka.
- Integrate AI capabilities into production applications with reliable APIs and backend services.
- Work on Life Sciences use cases and apply domain knowledge to solution design and implementation.
- Support model integration, retrieval workflows, and data platform alignment for enterprise AI solutions.
Skills Required:
- 5+ years of relevant experience in AI/ML and data engineering environments.
- Strong hands-on experience with Python, Generative AI, LangChain, LangGraph, FastAPI, and RAG.
- Experience designing AI/ML-enabled systems with scalable data architecture and production integration.
- Ability to work with Apache Spark, Hadoop, and Kafka in data-intensive environments.
- Experience building and supporting APIs and backend services for AI applications.
Good to Have:
- LLM fine-tuning, prompt engineering, and embedding models.
- Vector databases such as Pinecone or Weaviate.
- OpenAI API and Hugging Face Transformers.
- Cloud exposure across AWS, Azure, or GCP, including SageMaker, Azure ML, or Vertex AI.
- Life Sciences industry experience.
Education: Bachelor's degree in Computer Science, Data Engineering, or a related field; Master's preferred.