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.