AI Engineer driving design and implementation of AI features for nPlan, a construction tech startup. Collaborate with experts in a dynamic environment to reshape project intelligence.
About the role
- Gen AI Tech Lead implementing enterprise-grade conversational AI applications using NodeJS, Python, and Azure technologies. Leading development and integration of AI technologies for natural language capabilities.
Responsibilities
- Implement conversational AI application using NodeJS, Azure OpenAI and Python
- Integrate various AI technologies like OpenAI models, LangChain, Azure Cognitive Services (Cognitive Search, Indexes, Indexers and APIs etc) to enable sophisticated natural language capabilities
- Implementation of private endpoints across the Azure services leveraged for the application
- Implement schemas, APIs, frameworks and platforms to operationalize AI models and connect them to conversational interfaces
- Implement app logic for conversation workflows, context handling, personalized recommendations, sentiment analysis etc.
- Build and deploy the production application on Azure while meeting security, reliability, and compliance standards
- Create tools and systems for annotating training data, monitoring model performance, and continuously improving the application
- Mentor developers and provide training on conversational AI development best practices
- Build and productionize vector databases for the application on Azure cloud
Requirements
- 6-8 years of overall technology experience in core application development
- 2+ years’ experience leading development of AI apps and conversational interfaces
- Hands-on, implementation-centric knowledge of generative AI tools on Azure cloud
- Deep, hands-on and development proficiency in Python and NodeJS
- Hands-on expertise of SharePoint indexes and data/file structures (Azure SQL)
- Hands-on knowledge of Azure Form Recognizer tools
- Experience with LangChain, Azure OpenAI and Azure Cognitive Search
- Retrieval Augmented Generation (RAG) and RLHF (Reinforcement Learning from Human Feedback) using Python
- Vector databases on Azure cloud using PostgreSQL, Pinecone, FAISS, Weaviate or ChromaDB
- Prompt Engineering using LangChain or Llama Index
- Knowledge of NLP techniques like transformer networks, embeddings, intent recognition etc.
- Hands-on skills on Embedding and finetuning Azure OpenAI using MLOPS/LLMOPS pipelines
- Good to have - Strong communication, DevOps, and collaboration skills
Job title
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