Key Responsibilities
- Design, develop, and deploy Generative AI applications using state-of-the-art LLMs.
- Build and optimize RAG pipelines leveraging vector databases and enterprise knowledge sources.
- Develop prompt engineering strategies and evaluate model performance.
- Fine-tune, customize, and optimize foundation models for domain-specific use cases.
- Integrate AI solutions with cloud platforms and enterprise systems through APIs and microservices.
- Implement AI observability, monitoring, and evaluation frameworks.
- Develop scalable and production-ready AI applications following MLOps best practices.
- Conduct experimentation and benchmarking of LLMs, embeddings, and retrieval techniques.
- Collaborate with cross-functional teams to gather requirements and translate business problems into AI solutions.
- Stay updated on advancements in Generative AI, LLMs, agents, and multimodal AI technologies.
Key Responsibilities
- Design, develop, and deploy Generative AI applications using state-of-the-art LLMs.
- Build and optimize RAG pipelines leveraging vector databases and enterprise knowledge sources.
- Develop prompt engineering strategies and evaluate model performance.
- Fine-tune, customize, and optimize foundation models for domain-specific use cases.
- Integrate AI solutions with cloud platforms and enterprise systems through APIs and microservices.
- Implement AI observability, monitoring, and evaluation frameworks.
- Develop scalable and production-ready AI applications following MLOps best practices.
- Conduct experimentation and benchmarking of LLMs, embeddings, and retrieval techniques.
- Collaborate with cross-functional teams to gather requirements and translate business problems into AI solutions.
- Stay updated on advancements in Generative AI, LLMs, agents, and multimodal AI technologies.
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
- 6-9 years of experience in Software Engineering, Machine Learning, NLP, or AI development.
- Strong proficiency in Python and software engineering best practices.
- Experience with Generative AI frameworks such as:
- LangChain
- LlamaIndex
- LangGraph
- Semantic Kernel (preferred)
- Hands-on experience with LLMs including:
- GPT models
- Claude
- Llama
- Gemini
- Mistral
- Experience building RAG systems using vector databases such as:
- Pinecone
- FAISS
- Chroma
- OpenSearch
- Weaviate
- Familiarity with embedding models and semantic search techniques.
- Experience with REST APIs, microservices, and containerization (Docker, Kubernetes).
- Strong understanding of software design patterns and system architecture.